Coopetition for Mobile Service Provisioning

AMIRHOSSEIN GHANBARI COOPETITION FOR MOBILE SERVICE PROVISIONING

LICENTIATE THESIS IN INFORMATION AND COMMUNICATION TECHNOLOGY STOCKHOLM, SWEDEN 2016

Coopetition for Mobile Service Provisioning Is it about infrastructures, services or both? AMIRHOSSEIN GHANBARI

TRITA-ICT 2016:19 ISBN 978-91-7729-064-3

KTH 2016

www.kth.se

KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF INFORMATION AND COMMUNICATION TECHNOLOGY

Coopetition for Mobile Service Provisioning - Is it about infrastructures, services or both?

AMIRHOSSEIN GHANBARI

Licentiate Thesis in Information and Communication Technology School of Information and Communication Technology KTH Royal Institute of Technology Stockholm, Sweden 2016

TRITA-ICT 2016:19 ISBN 978-91-7729-064-3

KTH School of Information and Communication Technology SE-164 40 Kista SWEDEN

Akademisk avhandling som med tillstånd av Kungl Tekniska högskolan framlägges till offentlig granskning för avläggande av licentiatesexamen i Informations- och Kommunikationsteknik torsdagen den 25 augusti 2016 klockan 13.00 i Aula C, Electrum, Kungl Tekniska högskolan, Kistagången 16, Kista.. © Amirhossein Ghanbari, August 2016 Tryck: Universitetsservice US AB

iii Abstract As a means of enhancing our everyday lives, as well as a tool for digitalizing other industries, the Information and Communication Technology (ICT) industry has caused and experienced significant transformations during the past two decades. On one hand, this transformation relates to technological advances within ICT, and on the other hand it goes beyond the ICT ecosystem. Wireless ICT, as a subcategory of ICT, is also not an exception in this regard. Accordingly, if we consider Internet of Things (IoT) as the main enabler for digitalization, Machine to Machine communications (M2M) is then the technological enabler of IoT that represent the Wireless ICT in the process of transforming other industries. Looking into the role of ICT as a transformation tool, in this thesis we benefit from the concept of Smart City as a place where Wireless ICT participates for digitalizing other industries. We look into cases from smart city and investigate how smartification is taking place, where our findings show that wireless ICT mainly empowers other industries to provide M2M-enabled services for the citizens of smart cities. Consequently, this participation imposes major changes on the wireless ICT ecosystem itself. Therefore we study the changes that are forming the “future wireless ICT”, in the presence of other industrial service providers. In this process these service providers are considered as the new entrants to the wireless ICT ecosystem. In order to collect data, besides a thorough literature review, we have studied four cases from two major building blocks of smart cities: a) Intelligent Transportation Systems, and b) Digital Built Environment. We also expanded our data collection by performing semi-structured interviews with experts and decision makers, as well as participating in multiple projects and workshops. Accordingly, we have benefited from two major theories for analyzing the collected data; namely Actors-Resources-Activities (ARA) model and Porter’s Five Forces framework. The Analyses then have resulted in presenting cooperation and competition points in the future wireless ICT. We argue that traditional wireless ICT actors (i.e. mobile network operators & telecom equipment vendors), first have to adopt value co-creation methods in new businesses they enter, such as IoT in smart cities. This means cooperation among these actors, which takes the Seller-Buyer relationship to the next level that is Supplier-Customer, in which both sides collaborate on co-creating the value. Accordingly, we argue that the linear processes of creating value, adopted from traditional wireless ICT ecosystem, are inefficient in these new markets and value networks must be adopted instead. We discuss business relationships among major involved entities in the new value networks, while striving to describe their complexity. As a result, we introduce “vertical coopetition” as a dominant business relationship among traditional actors, and new entrants in future wireless ICT. As the main contribution of this thesis, we finally discuss the logic behind vertical coopetition while comparing it with the other (better-known) description of coopetition, which is cooperation among competitors (horizontal coopetition).

v Sammanfattning Som ett sätt att förbättra vår vardag, och som ett verktygför digitalisering av andra branscher, har informations- och kommunikationsteknik (ICT) industrinbådeorsakatochupplevtbetydandeomvandlingarunderdesenaste tvådecennierna. Åenasidanavserdennaomvandlingtekniskaframsteginom ICT,ochåandrasidangårdetutanförICTekosystemet. TrådlösICT,somen undergruppavICT,ärintehellerettundantagidettaavseende. Följaktligen, omvianserattsakernasInternet(IoT)ärdenhuvudsakligamöjliggörarenför digitalisering, då är maskin-till-maskin kommunikation (M2M) den tekniska möjliggörarenavIoTsomrepresenterartrådlösICTiprocessenattomvandla andra industrier. Om vi betraktar ICT som ett verktyg för omvandling så kan vi i denna avhandling dra nytta av begreppet “Smart stad” som en plats där trådlös ICT medverkar för digitalisering av andra branscher. Vi undersöker fall av smarta städer och undersöker hur denna “smartification”s kero chd ärvåra resultat visar att trådlös kommunikationsteknik främst möjliggör för andra branscher att tillhandahålla M2M relaterade tjänster och lösningar för medborgare i smarta städer. Följaktligen innebär detta stora förändringar av ekosystemer för trådlös ICT. Därför studerar vi förändringar som bidrar till att skapa framtida trådlös ICT i närvaro av andra tjänsteleverantörer inom andra sektorer. I denna process ser vi dessa tjänsteleverantörer som de nya aktörerna inom det ekosystemet för “trådlös ICT”. Förutomlitteraturstudierbaserasdatainsamlingenpåfyrafallstudierinom två av de viktigaste byggstenarna inom smarta städer. Datainsamlingen utgörs av intervjuer med experter och beslutsfattare samt deltagande i projekt och workshops om M2M. Analysen baseras på två olika “teorier”, ARA (aktörer-resurser-aktivititeter)samtPortersramverkmedolikatyperavmarknadskrafter. Dettaresulterarislutsatserkringsamarbeteochkonkurrensför framtida trådlös ICT. Ivårstudiehävdarviattdetraditionellaaktörernasåsommobiloperatörer och leverantörer av telekomutrustning först måste ta till sig värdeskapande i samarbete med andra när man skapar nya affärer, ett exempel är IoT i smartastäder. Dettainnebärattsamarbeteavtypensäljare-köpareutvecklas till en annan nivå vidare i form “tillhandahållare”-“kund”, varvid båda sidor samverkar för att skapa värde. Därför hävdar vi att de linjära processer för att skapa värde, som används inom traditionell trådlös kommunikation och dessekosystem,ärineffektivapådessanyamarknaderochmaniställetmåste utveckla nya värdenätverk. Vidare diskuteras affärsrelationer mellan stora inblandadeaktörerinyatyperavvärdenärverk,dettaisyfteattbeskrivaderas komplexitet. Som ett resultat introducerar vi vertikal “coopetition” som en dominerande affärsrelation för både traditionella och nya aktörer. Slutligen diskuteras, som ett väsentligt forskningsbidrag i avhandlingen, affärslogiken bakomvertikal“coopetition”genomattjämföradettamedmervälkändform av “coopetition”, nämligen samarbete mellan konkurrenter, dvs horisontell “coopetition”

To Nosrat, and Jamshid

ix

Acknowledgements Two years into the PhD program in Tele-Economics, I have learned much more than what I was expecting. I am very grateful of the opportunity to study this interdisciplinary topic, specially because of the different supervision that I have received. I found my work place, a relaxed, open, and involving environment that let me follow what I assumed is correct. Many names but of course, first of all, I am deeply grateful to Associate Professor Jan Markendahl for his special guidance and caring. I appreciate his invaluable help and his knowledge that he shared with me, and I hope that we keep having our enthusiastic and direct discussions. I am also deeply grateful to Professor Jens Zander, my co supervisor, for giving me the opportunity to work under his supervision. I would also like to thank Andrés Laya for many things that I have learned from him. Besides, I am grateful to the people of RS Lab that provided me with an excellent atmosphere to do the research that I liked to do. Finally, I am thankful to the person who I started this journey with, and the one who I followed.

Amirhossein Ghanbari August 2016

Contents Contents

xi

List of Figures

xiii

List of Tables xv List of Acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii

I Thesis Overview 1 Introduction 1.1 Background . . . . . . . . . 1.2 Traditional Telecom Actors 1.3 General Problem Area . . . 1.4 Thesis Outline . . . . . . .

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2 Literature Review 15 2.1 The Three Areas of Study . . . . . . . . . . . . . . . . . . . . . . . . 15 2.2 Coopetition as a Tool for Describing Relationships . . . . . . . . . . 17 2.3 Where is The Research Gap? . . . . . . . . . . . . . . . . . . . . . . 22 3 Problem Description 25 3.1 Value Co-Creation in Light of Coopetition . . . . . . . . . . . . . . . 25 3.2 Discussion on Research Questions . . . . . . . . . . . . . . . . . . . . 27 3.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 4 Methodology and Theoretical Foundation 37 4.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 4.2 Theoretical Foundation . . . . . . . . . . . . . . . . . . . . . . . . . 41 5 On Co-Creation of Value to Support Value Networks 51 5.1 Techno-Economic Research in Telecommunication . . . . . . . . . . . 51 5.2 Value, Value Chains and Value Networks . . . . . . . . . . . . . . . . 53 xi

xii

CONTENTS 5.3

Telecommunication Value Network in Smart City . . . . . . . . . . .

6 Case Studies and ARA Analysis 6.1 M2M in Smart Cities . . . . . . . 6.2 Case Studies . . . . . . . . . . . 6.3 ARA Analysis of Wireless ICT in 6.4 Shared Indoor Cellular Networks

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7 Analysis and Discussion 7.1 Analysis of Competitive Forces in Telecom Industry sented Case Studies and Observations . . . . . . . . 7.2 Coopetition Points in Future Telecom . . . . . . . . 7.3 Discussion of The Results . . . . . . . . . . . . . . .

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based on Pre. . . . . . . . . . . . . . . . . . . . . . . . . . .

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8 Conclusions 89 8.1 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 8.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

II Paper reprints

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9 Shared Smallcell Networks Multi–operator or Third party solutions -or both?

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10 Tele-Economics in MTC: what numbers would not show

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11 Repositioning in Value Chain for Smart City Ecosystems -a Viable Strategy for Historical Telecom Actors

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12 MTC Value Network for Smart City Ecosystems

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13 Value Creation and Coopetition in M2M Ecosystem - The Case of Smart City

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Bibliography

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List of Figures 1.1 1.2 1.3

Simplified Mobile Telephony value chain (Ghanbari et al., 2015b)

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The focus of our literature review on coopetition

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What to show in this thesis, and how to show it.

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Qualitative research steps in this thesis

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Interactions between wireless ICT and economics (Laya et al., 2015)

Traditional Value Chain for MNOs and TEVs

The focus of our literature review on value creation

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Value chains and value networks (Laya et al., 2015)

Simple Smart City value chain and sampled position of actors in the value chain (Based on Ghanbari et al. (2015b))

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Where theories are applied in the thesis

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The disruption of value generation and the importance of OTT services Tesla vs. Volvo (Ghanbari et al., 2016)

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Joint Venture and Merger value networks in network sharing (Based on Ghanbari et al. (2015b))

New actors in indoor cellular networks provisioning (Markendahl and Ghanbari, 2013)

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xiv 8.1 8.2

List of Figures Co-creation of value in future telecom

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An instance of merging advertisement value network and telecom value network

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List of Tables 4.1 4.2

Participated projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Participated applications for projects . . . . . . . . . . . . . . . . . . . .

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Who is capable of what activity? . . . . . . . . . . . . . . . . . . . . . .

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Activities that traditional MNOs are likely to perform . . . . . . . . Activities that traditional TEVs are likely to perform . . . . . . . . Activities that SPs are likely to perform . . . . . . . . . . . . . . . . Vertical vs. Horizontal relationships in traditional mobile telephony

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xv

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LIST OF ACRONYMS

List of Acronyms 5G

Fifth generation of mobile networks

EU

End User

ICT

Information Communication Technology

IoT

Internet of Things

M2M

Machine to Machine communications

MNO

Mobile Network Operator

MSP

Managed Service Partner

MTC

Machine Type Communications

OTT

Over The Top

SP

Service Provider

TEV

Telecom Equipment Vendor

xvii

Part I

Thesis Overview

1

Chapter 1

Introduction 1.1

Background

It is well known that the information and communications technology (ICT) ecosystem has experienced a significant transformation over the past two decades (Christensen et al., 2013; Fransman, 2010). Driven by rapid technological advances, changing societal preferences, and shifting economic and regulatory conditions, ICT firms had to continuously seek ways to improve existing value propositions and create and deliver new ones in order to grow and survive (Iansiti and Richards, 2006). These complex dynamics continue to persist and have led the ICT ecosystem to become one of the most dynamic and fiercely competitive business environments (Basole et al., 2015). At the same time that the ICT industry is undergoing major transformations, it is also changing other industries as well. By acting as a tool for transforming other industries, ICT is aiming to better utilize resources as well as sustaining processes in various industries. As a consequence, a major reason for the changes happening in ICT ecosystem is its integration with other industries. This phenomenon can be better described by highlighting the difference between “technology push” and “market pull” (Bouwman et al., 2005). Therefore, if we consider different non-ICT industry service providers as the new customers for ICT, the only way to satisfy these customers would be offering services by listening to their needs and what markets “pull”, rather than “pushing” for new or existing technologies. This means that in order to act as a tool to transform other industries, ICT requires to change in order to dynamically adapt the new requirements of other industries. In the aforementioned fast pace changes of the ICT industry, different actors appear (new actors) and disappear in its ecosystem. A part of the adaptation then means changes for those actors who want to stay in the ecosystem. As a result, traditional actors do not necessarily behave as they used to do in the ecosystem, and new entrants also do not necessarily take previously created roles for traditional actors. Consequently the Wireless ICT (Telecommunication industry), as a subcategory of ICT, is also going through this transformation; a transformation 3

4

CHAPTER 1. INTRODUCTION

that would result in reformation and creation of a new telecom in the future. Let us call this new Telecom, “future Telecom industry”. On the supply and demand side Since ICT is transforming other industries, by focusing on Wireless ICT, the 5G concept best exemplifies this transformation tool. The fifth generation wireless system (5G) is the next coming major phase of Wireless ICT that “is positioned to address the demands and business contexts of 2020 and beyond. It is expected to enable a fully mobile and connected society and to empower socio-economic transformations in countless ways many of which are unimagined today, including those for productivity, sustainability and well-being. The demands of a fully mobile and connected society are characterized by the tremendous growth in connectivity and density/volume of traffic, the required multi-layer densification in enabling this, and the broad range of use cases and business models expected” (5G Alliance, 2015). Possibly in 2020 (less than 5 years from now), we will witness many driverless cars and pilotless drones. To deal with the influx of so many new devices that will use internet, there will be definitely a demand for a new level of wireless connectivity; where the new level of wireless connectivity seems to be the promise of 5G. But what does 5G has that previous generations (e.g. 4G) do not have? The answer is to think of 5G as of an improved generation, not only technically but also in the business domain; a sliced network that accommodates industry verticals and helps them to horizontalize their operation. This means that 5G is more about the demand and less about a push from technology and especially not only about telecommunication technology. In fact, “industrial customers do not actually want 5G systems; these customers just want to solve problems in their industries” that means full cooperation among multiple enablers1 . Focusing more on service provisioning, and Everything as a Service (XaaS), connectivity then becomes a service enabler, while not long ago connectivity was the only service. This means that the “future telecom” is about to expand its market, more, to other industries as well as creating new market/s. Therefore, if this new market for wireless ICT is expected to happen, value2 needs to be co-created together with actors of other industries. The value co-creation can happen in two ways: (a) Internally, which is among telecom actors, and (b) Externally, which is among telecom actors and actors of the other industries. The question is then how would be the relationships among firms in this new setup. In the process of value creation, it is interesting to see what are the possible relationships among these different actors (both internal and external), compared to how it has been done for years. To examine this, in this thesis, we choose an area to put Wireless ICT into a context: Smart City. Smart City ecosystem is quite complex and understanding the role of Wireless ICT actors in this ecosystem seems to be necessary for clarifying the co-creation process. The traditional telecom 1 Simon

Saunders, Access Technology Principal at Google, at Johannesberg Summit 2015. the context of our research, we define “value” as a measure of the benefit provided by a good or service to an actor. 2 In

1.2. TRADITIONAL TELECOM ACTORS

5

actors, i.e. Mobile Network Operators (MNO) and Telecommunication Equipment Vendors (TEV) then become the “usual suspects”. A third group of actors also emerge in this telecom co-creation process: Service Providers (SP). In this setup SPs comprise non-ICT industries’ service providers offering telecom-enabled services (we call them SP in this thesis) and Over the Top (OTT) Service Providers. On the coopetition side Different types of business relationships exist among traditional telecom and other involved actors in the smart city ecosystem. These relationships mainly comprise cooperation and competition. In this ecosystem, due to its different nature compared to traditional telecom ecosystem, wireless ICT actors act differently compared to their “home” ecosystem that is mobile telephony. At the same time, the presence of new entrants cannot also be overlooked since it affects the relationships in the ecosystem quite intensively. Competition and dynamic changes cause and demand new behaviors among the actors. This highlights the need for focusing on (a) Cooperating with competitors, and (b) Competing with cooperators. These two types of business relationships are referred to as Coopetition. An instance of such relationships is the vertical collaboration among MNOs and TEVs when MNOs have outsourced their network operation centers to TEVs. The same TEVs have become competitors for MNOs later on in different setups and businesses. When it comes to presence of new entrants, an example on vertical cooperation patterns is when MNOs collaborate with new third party network operation outsourcees. This example shows the presence of new entrants and the important roles they acquire in such an ecosystem. We can conclude on coopetition by saying that for traditional Wireless ICT actors; cooperation with competitors has been around for sometimes in different formats. But competing with cooperators is not a common business relationship for them.

1.2

Traditional Telecom Actors

Mobile Network Operators (MNO)3 is the first group of actors that we study in this thesis. In a traditional business model, MNOs design their own network, own their infrastructure, operate the network and offer services on top of it; a voice-revenue dependent business. This business mainly has been performed in a Business to Customer (B2C) setup. At the same time MNOs have mainly offered connectivity based on a best effort regime while they have mainly seen handling capacity and coverage as the major challenge for themselves. This means that they have to provision the increasing data traffic as well as future demand. Along this business model MNOs have seen that lack of some vital resources has become a big barrier for them to overcome the aforementioned challenge. This means collaborating with other actors of the telecom ecosystem. 3 Examples

are China Mobile, Vodafone, AT&T Mobility, Telefónica, etc.

6


Now with the data provisioning, since the revenues associated with data do not comply with the pattern of increasing data usage in mobile networks, MNOs started to look for new revenue streams in order to sustain their growth. As a result, MNOs have started expanding their business models by offering “services” besides their usual competences. This complicated approach has then forced them to think of possible cooperation patterns in order to benefit from horizontal integration, instead of being vertically integrated. The MNOs’ business transactions have also gone through changes during the time. They have transformed from only B2C transactions to “Business to Business” (B2B) transactions. The B2C setup mainly corresponds to the voice-revenue business and the B2B setup comprise efforts such as M2M service offerings. One major consideration here is the fact that MNOs have been offering connectivity in a “best effort” basis, which is not acceptable for some Business customers of the B2B setup. Examples can be Utility communications, tele-communications for Remote Surgery, etc. The second group under study is Telecommunications Equipment Vendors4 (TEV). TEVs in their traditional business model are used to manufacture the mobile network equipment and sell to MNOs. These have been typically products that are needed for mobile and fixed communications, several generations of radio networks, IP and transmission networks, core networks, and cloud. Over years, with the increase of complexity in the telecommunication systems, TEVS have offered solutions for mobile and fixed communication, such as measurable performance improvements in MNOs’ business processes, with software that is scalable, configurable and that provides end-to-end capabilities. With regards to the need of MNOs to focus on their core business, TEVs have started to offload some operational pressure from MNOs as well. In this business model TEVs, also act as Managed Service Partners (MSP) where they offer network rollout services and professional services (i.e., managed services, as well as network design and optimization services). This way they sometimes take over controlling a MNOs’ network on their behalf and operate the network. Over the time, the aforementioned activities have escalated the TEVs business towards enhancing Operations Support Systems (OSS) and Business Support Systems (BSS) to develop and deliver software-based solutions for MNOs. These competences have then encouraged TEVS to offer OSS and BSS, TV and media solutions, as well as solutions and services for the emerging m-commerce ecosystem. Utilizing gained competences as well as expanding business into various markets, TEVs now are able to supply other industries besides telecommunication. Since the role of supplier has long been in the TEVs agenda, it is not far from reach to serve other industries’ service providers with ICT/Telecom solutions.

4 Examples are Ericsson AB, Nokia Solutions and Networks, Huawei Technologies Co, and ZTE Corporation.

1.3. GENERAL PROBLEM AREA

Figure 1.1:

7

Simplified Mobile Telephony value chain (Ghanbari et al., 2015b)

Traditionally, these two main actors of the telecommunication industry have been offering their services in vertically integrated models5 . This model then was translated to a simple value chain for mobile telephony (Figure 1.1). In this value chain, the TEVs were in charge of supplying MNOs with equipment for deploying cellular networks, and possibly operating those networks on behalf of MNOs. At the same time, MNOs provisioned services and managed Customer Relations and offered the final service to end users. In this model the collaboration among MNOs and TEVs was quite clear where TEVs mainly performed the role of supplier and the MNO was the direct customer (Figure 1.2).

Figure 1.2:

1.3 1.3.1

Traditional Value Chain for MNOs and TEVs

General Problem Area Cooperation and Competition among actors in Wireless ICT Ecosystem

Considering ICT as a tool for transforming other industries, the vertical integration for MNOs and TEVs is not as simple as used to be any more. As non-ICT industries become more complex and ICT services being offered to them need to utilize many different competences, there is a need for different ICT actors to rely on the expertise, resources and competences of each other rather than being vertically integrated. Narrowing down the scope to wireless ICT, this means that new wireless ICT offerings and services will be mixed with the customers’ services, resulting 5 Adaptation of “vertical integration” within industries mainly originates from the idea of making most profitability.

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in offering final products/service outside the scope of TEVs’ and MNOs’ competences. At the same time, requirements from different industries as new customers of wireless ICT actors will also vary. New actors also emerge who might have same or different agenda compared to traditional wireless ICT actors. Taking Michael Porter’s five forces into account (Porter, 2008a), entrance of new players also provokes the aforementioned complexity. It was not long ago that the telecom ecosystem had been formed by participation of a handful of actors. Now the entrance of Service Providers and OTT service providers is yet another reason for complication. As a result, the telecom ecosystem no longer just consists of wireless ICT actors. Actors (mainly Service Providers) from other industries also co-exist with telecom actors in the new ecosystem and form the future telecom ecosystem. As a result, the complex newly emerged ecosystems, which include ICT as a supplier-enabler and other industries, needs to be simplified and understood. Therefore we utilize three theories for analyzing this complex ecosystem: ActorsResources-Activities (ARA) framework, Porter’s Five Forces (P5F) analysis, and accordingly Coopetition. It should be mentioned that in this thesis we follow a network perspective for our analyses, which means that business interactions among firms for the sake of cooperation are considered as the key to success for the firms. Therefore the ARA model, which follows the same logic will embody the main analysis of this thesis regarding cooperation. On the other hand, since it is hard to believe that any firm does not follow its specific goals and objectives, we believe that it is necessary to look into the network from each firm’s point of view when we discuss cooperators, as well as competitors. This means that, beside being part of a network, each firm in its essence is a solo entity that has its own objectives and business goals that based on them interacts with other actors. Hence, we will also benefit from P5F model that has a single firm perspective, for the sake of identifying competitors and cooperators. As mentioned before, we believe that business interactions are keys to success, while keeping in mind that simultaneous cooperation and competition happen6 . Hence, our discussions are not purely on cooperation (that ARA assumes), or purely on competition (that P5F assumes). Eventually, based on the combination of ARA and P5F, we discuss simultaneous cooperation and competition among cooperators, and expand it to the coopetition theory. This new angle of coopetition is called “vertical coopetition”. The ARA model (Håkansson and Johanson, 1992) is a framework that suggests processing three aspects for describing the content of business relationships: Actors, Activities, and Resources. The P5F model helps us finding cooperation and competition patterns (Porter, 2008b). And, the coopetition model then discusses the relationships among competitors and cooperators that happen simultaneously (Bengtsson and Kock, 2000). Cooperative competition or coopetition is a phenomenon that two firms cooperate and compete with each other at the same time. 6 The contradictory nature of ARA model and P5F and why they are used in this thesis are better explained in chapter 4.


9

We refer to Coopetition as either cooperation between competing firms leading to possible win-win conditions (Basole et al., 2015); or competition between cooperative firms that in literature is often called vertical coopetition. By competing firms we refer to those entities that can provide the same services for the end user, whether the end user is a business customer or private. The ecosystem considered in this study, mainly, includes the presence of traditional telecom actors (i.e. MNOs & TEVs), and industry (non-ICT) service providers offering telecom-enabled services (Service Providers), End Users (EU), and Over the Top service providers.

1.3.2

Competition and Cooperation Areas

In this thesis, while we study ICT as a transformation tool for other industries, we narrow down the scope of our research from ICT to mobile service provisioning, which directly relates to wireless ICT. This leads our discussions to the telecom industry–or the so called Wireless ICT–, mobile service provisioning, Business to Business (B2B) relations among actors and other industry verticals, and major telecom actors. Since in this thesis we have a network perspective, we pick the three major actors from the future telecom industry that directly participate in mobile service provisioning and analyze the relationships among them in the business network. These actors are MNO, TEV, and SP7 : 1. Mobile Network Operator (MNO) is a provider of mobile services based on wireless communications. A MNO typically owns all required elements (e.g. wireless network infrastructure, radio spectrum license, core network, CRM systems, etc.) and delivers services directly end user. Examples are China Mobile, Vodafone, AT&T Mobility, Telefónica, etc. 2. Telecommunications Equipment Vendors (TEV) refers to a group of telecom actors that were originally supplier for MNOs. They typically offered products that are needed for mobile (different generations) and fixed communication, transmission and IP networks, core networks and cloud network. More recently, these firms also focus on providing solutions such as rolling out professional services such as managed services, network optimization, network design for their prime customers that are MNOs, as well as provisioning telecom-enabled service to other industries in the process of digitalization8 . Examples are Ericsson, Nokia Solutions and Networks, and Cisco. 7 The reason that we do not include OTT service providers in this list is that, in this thesis, we do not look into the changes that OTT service providers cause on the Wireless ICT ecosystem and the process of value creation; rather we look into the emergence of SPs as a new actor in Wireless ICT ecosystem. This means that the effect of OTT service providers emergence on the process of value creation and the relationships among actors based on their presence require separate analysis and discussions; although we believe that majority of our presented analyzes would fit those discussions. 8 Digitalization refers to making “things” from industries less dependent to physical space in the process of transforming those industries by ICT. According to Joachim Sachs, RST group planning conference 2016, Skåvsjöholm

10

CHAPTER 1. INTRODUCTION 3. Non-ICT industries’ Service Providers (SP) are the actors of different industries that are subject to ICT transformation. These industries can vary from Transport, Utilities, etc. to Music. These actors have been offering solutions within their industries to end users or other actors (as suppliers) for years and now with the emergence of ICT they seek better performance and/or new opportunities. The services that these actors offer (that are of our concern in this study) are the ICT-enabled (or more specifically wireless ICT-enabled) services. These services could have not happened unless they have merged their value creation process with the telecom and create value networks. Examples are Scania, Duke Energy, and Electric and Musical Industries Ltd.

Looking into how ICT transforms other industries, if we consider Internet of Things (IoT) as the main enabler for this transformation–digitalization–,we focus on a segment in telecom industry that represents services for other industries, which is Machine to Machine (M2M) communications9 . Consequently, according to 3GPP, the segment of M2M carried over cellular networks is often called Machine Type Communications (MTC)(3GPP, 2014) we may sometimes refer to MTC instead of M2M. The other closely related concept, IoT, is often regarded as a set of principles, technologies and systems associated to Internet-connected objects (Holler et al., 2014). In contrast to MTC and M2M, IoT includes the connection and access to the broader Internet (Laya et al., 2015). The term was first coined in 1999 by Kevin Ashton even before the dotcom bubble (Wood, 2015) to describe a “world of seamless connected devices that would save us time and money”, based on the interconnection of the physical world with the virtual world of Internet (Mazhelis et al., 2012).

Figure 1.3:

Major coopetition areas in telecommunication ecosystem

Since we are looking into wireless ICT’s presence as a tool in other industries, we chose to pick a context for telecom industry’s presence. Hence we look into Smart City context as a place where ICT integrates into other industries and makes 9 Machine to machine communications refers to communications among autonomous devices with minimal human intervention.


11

them smart and serves as a major enabler for smart solutions. We categorize three interrelated areas to study: M2M communications, Smart City, and Network sharing. As described before, M2M communications is how Wireless ICT helps as an enabler for digitizing other industries in Smart cities, and Network Sharing is an area in which trends of coopetition among telecom actors have been around in recent years. As illustrated in Figure 1.3, we discuss M2M communications in Smart Cities while using the knowledge and understanding from network sharing and apply it on describing the cases from the other two areas. It should be mentioned that same set of traditional actors exist in all three area, although when it comes to different businesses the same set of actors position themselves differently in the ecosystem; As an instance, in the case of Mobile Telephony and M2M service provisioning, MNOs serve different customer segments. How these three areas will be used in this thesis, in brief: • M2M communications will represent the new ecosystem for wireless ICT actors where changes are imposed to the wireless ICT ecosystem. • Smart City is then the place where the role of telecommunication (Wireless ICT) as a tool for transforming other industries is highlighted, while non-ICT industries merge into wireless ICT ecosystem. • Network Sharing will represent a viable case where telecom actors have been performing various coopetition models for some years, while the presence of new entrants to the market also caused changes to inter-firm relationships and formation of value chains10 .

1.3.3

Research Questions

In this section a set of research questions are presented in order to clarify the direction of research in different steps. The questions are based on the general problem area introduced earlier. We will discuss the questions and how they can help this study in section 3.2, soon after we introduce the specific problem that “this” thesis is going to tackle (Chapter 3). The main question of this thesis is to clarify where the competition and cooperation is in future mobile service provisioning. Since the above statement and question is not easy to resolve, it should be elaborated: RQ1 : Why do competitors in mobile service provisioning have to cooperate? RQ2 : Why do cooperators in mobile service provisioning compete? RQ3 : How would repositioning in the telecom value chain benefit traditional actorsof telecommunication industry? 10 Formation of first instances of value networks replacing value chains in cellular network ecosystem is a consequence of emerging new actors.

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1.4


Thesis Outline

In chapter two we introduce the related work in the context of literature review. We first look into relevant literature in the three coopetition areas; namely Network Sharing, M2M communication, and Smart city. Next we present works done by scholars in the area of coopetition and contextualizing coopetition on one hand, and the area of value networks and value creation on the other hand. We also present preliminary related works on coopetition in ICT as well as Value Networks in ICT. Eventually, at the end of this section, we put the value discussions of the value networks and coopetition in the context of M2M in Smart City and present the identified research gap. In chapter three first we narrow down the introduced general problem, based on the identified gap and present the specific problem that this thesis would contribute to resolve. In order to clarify the direction of research in different steps, previously, we presented three research questions in section 1.3.2, which will be discussed an elaborated in section 3.2. Next we present the contribution done via multiple research publications done by the author, and discuss how they are relevant to this thesis. Eventually we present the contribution of the thesis based on reprinted papers, attached. In chapter four, we first discuss the general methodology used in this thesis, then we discuss theoretical foundation for the discussions and analyzes. We introduce the theories being used and define which parts we adopted for the analysis and what is it that we modified /developed. The theory modification/development is due to the fact that some of the applied theories, originally, lack some properties required for analysis of our cases. This can be solved with some modifications and add-ons. In chapter five we discuss the role of wireless ICT in other industries as a transformation tool and the importance of performing a study in telecommunication from an economic point of view. We use concepts from industrial economy to introduce the importance of formation of new telecom value networks in the presence of other industries, and how linear telecom value chains are unable to serve new ecosystems. For this matter we benefit from a known interdisciplinary school of research called techno-economics. We also discuss why it is important to co-create value in form of value networks. We will use these discussions to show how traditional telecom actors play different roles in new markets compared to their activities in Mobile telephony. Eventually we discuss the role of future telecom value network in Smart Cities. In chapter six we introduce two cases in mobile service provisioning; M2M services in Smart Cities, and sharing indoor cellular networks. In the former case we first introduce the case studies that form the foundation of the rest of the thesis. In this chapter, based on the secondary data, we identify telecom activities in MTCenabled services and propose a framework to study these activities. We then apply the framework on the smart city case and identify telecom activities in smart city. We then define major resources required for performing these activities. Eventually

1.4. THESIS OUTLINE

13

we propose a set of abstract actors in form of an abstract value network. In chapter seven we analyze the business relationships among different actors of the M2M/MTC value network. We question what would happen if any of the groups of actors under study–MNOs, TEVs, and SPs–perform either of the activities of the proposed activity framework by applying Porter’s Five Forces (P5F) model as a checklist for identifying important business relationships for the focal firm. Next we determine the positions in which MNOs, TEVs, and SPs would possibly compete with each other and/or cooperate. Eventually we discuss the relationships among actors based on the coopetition model. Most of this chapter is then dedicated to discuss the implications of our findings (results). The discussions are presented alongside the analysis. Finally, in chapter 8, we conclude the thesis by answering the research questions, as well as the question of the title of the thesis and introduce the future work.

Chapter 2

Literature Review In this chapter we first introduce briefly what we refer to when mentioning any of the three coopetition areas, and present related works done by scholars in each area. Since our study is focused on investigating the business relationships among firms in the future telecom ecosystem, next we present a further thorough literature review on the following two areas: Coopetition, and Value Networks. This step of the literature review is done by focusing on the general concern of this thesis that is the business relationships among firms. For the second part of the literature review we follow an “onion approach”. This means that we first review the literature in the general area of the field as the first layer. Next we dive deeper towards the core and cover a more specific layer related to our study, and follow this approach till we cover the specific topic of the thesis. This approach is better illustrated in Figures 2.1 and 2.2. In order to perform a thorough literature review we conduct our “onion approach” for both two aforementioned areas: Coopetition, and Value Networks. On one hand we have chosen coopetition as the concept of simultaneous cooperation and competition among firms; while narrowing it down to coopetition in ICT. On the other hand, we chose the process of formation of value networks based on the interactions among firms and the creation of the value itself for describing the business relationships in the ecosystem. We believe that the combination of these two areas together with the aforementioned coopetition areas will give us a good overview for conducting our research. At the end of this section, we overlap and relate the conducted literature review and identify the research gap.

2.1 2.1.1

The Three Areas of Study Machine to Machine Communications

M2M, MTC and IoT mainly entail complementing concepts but are quite often used interchangeably (Laya et al., 2015), where the three terms imply the notion of connected autonomous devices. M2M is typically defined as the set of wireless and 15

16

CHAPTER 2. LITERATURE REVIEW

wired communication between mechanical or electric devices (Turner et al., 2013) or communication between remote machines and central management applications (Whitehead, 2004). Another definition of M2M considers it as all the information and communication technologies able to measure, deliver, process, and react upon information in an autonomous fashion (Anton-Haro and Dohler, 2014). Considering MTC as the working terminology used by 3GPP, it is often regarded as the segment of M2M carried over cellular networks (3GPP, 2014; Jain and Hedman, 2012). M2M and MTC are at times considered synonyms (Laya et al., 2015; Shariatmadari et al., 2015; Taleb and Kunz, 2012). It can be argued that M2M–and MTC–are communication enablers for the broader concept of the IoT. Recent advances in this field have shown a strong potential on smartification of services and products by means of ubiquitous communications (Chen, 2013). The importance of M2M/IoT as a major enabler for smartification is discussed in the literature (Balakrishna, 2012; Elmangoush et al., 2013; Sanchez et al., 2014; Wan et al., 2012). Hence, we consider Smart City as a platform for implementing M2M/IoT enabled solutions by different industries involved in the process of offering smartized products and services.

2.1.2

Smart City

A common definition of Smart City is the use of ICT to sense, analyze and integrate the key information of core systems in running cities in order to optimize existing services, while offering new possible services to end users. Smart City itself is often considered as a subcategory of Sustainable Smart City, which is defined as an innovative city that uses ICT and other means to improve quality of life, efficiency of urban operation and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social and environmental aspects. We consider that a Smart City consists of five major building blocks (Correia and Wünstel, 2011): 1. Economic, Social & Privacy Implications 2. Developing E-Government 3. Health, Inclusion and Assisted Living 4. Intelligent Transportation Systems 5. Digital Built Environment In order to make an existing city Smart or create a Smart City based on these five block items, two approaches exist (Breuer et al., 2014; Walravens et al., 2014) : Top Down, and Bottom Up. Top Down approach uses an ICT system that has an overview on all urban activities as well as the tools to (automatically) interact with infrastructures, gather vast amounts of data and adjust parameters to predefined

2.2. COOPETITION AS A TOOL FOR DESCRIBING RELATIONSHIPS

17

optima (Dirks et al., 2009). This approach places strong emphasis on optimization through technology (Vaughan, 2013). The Bottom Up approach then is, foremost, about the “Smart Citizen” (Hemment and Townsend, 2013). This approach, rather than working towards centralization, takes a decidedly distributed approach, supporting and accepting some form of chaos (Lindsay, 2011). Since both aforementioned approaches have their own deficits, a better solution is a proper mix of both Top Down and Bottom Up, compromising absolute perfections of each approach. Hence, considering the important role of ICT in smartification of cities (ETSI, 2014a,b), we can consider M2M as an enabler for Smart solutions in the bottom up approach; as well as means of providing smart top down solutions (ETSI, 2015). IoT/M2M/MTC in the context of Smart City covers a broad area that includes many different industries. In order to narrow down the scope, in this thesis we will focus on how telecom actors see opportunities in this concept and where do they position themselves in the smart city value network to benefit most. This positioning strategy for MNOs and TEVs corresponds to the repositioning concept. This means that these actors may need to perform some roles that they traditionally do not perform, and allow some other actors to carry out such activities.

2.1.3

Network Sharing

When it comes to cellular networks, and the relations among different actors in this setup, there are three major categories possible to study: Urban Outdoor networks, Indoor networks and rural networks. If we consider network sharing as the prime coopetition paradigm in this context, it can be discussed under all three categories where the latter two somehow follow more similar patterns. On one hand, scholars mainly consider sharing base stations, network sites, radio equipment, and spectrum as common strategies (Beckman and Smith, 2005; Frisanco et al., 2008; Khan et al., 2011). On the other hand, regarding indoor and rural networks, the presence of new entrants such as Facility Owners, and third party operators and their effect on the relations among actors is discussed as the major difference compared to Outdoor networks (Khan et al., 2011; Markendahl, 2011; Markendahl and Makitalo, 2007; Markendahl et al., 2012; Mumtaz et al., 2012; Offergelt et al., 2011). The benefits, drivers, drawbacks and risks with shared networks are also discussed by Markendahl and Mölleryd (2012) and are quite well understood.

2.2

Coopetition as a Tool for Describing Relationships

The word coopetition was first coined by Kirk S. Pickett of the Sealshipt Oyster System in 1911, while he intended to describe the business relations among its customers (dealers): “You are only one of several dealers selling our oysters in your city. But you are not in competition with one another. You are co-operating with one another to develop more business for each of you. You are in co-opetition, not

18


in competition” (Cherington, 1913). The famous “Co-opetition” book by Brandenburger and Nalebuff (2011) then introduced coopetition as a consequence of both war and peace in businesses and raised attention for the concept, years after Pickett. Different scholars have looked into coopetition dynamics (Khanna et al., 1998; Tsai, 2002), its foundations (Dagnino and Padula, 2009) and the relevance of coopetition as a research problem (Ginevi ius and Krivka, 2008), while more recently the interest on putting coopetition into the context of specific businesses has gone higher.

2.2.1

Coopetition in The Context of Specific Industries

While contextualizing coopetition, scholars mainly have focused on coopetition as a tool for enhancing business by sharing knowledge, reducing costs, absorbing skills, boosting utilization and enhancing economic benefits (Battista and Giovanna, 2002; Gnyawali and He, 2006; Gnyawali and Park, 2011; Hamel et al., 1989; Lado et al., 1997). At the same time, coopetition as a business strategy (Fuller and Porter, 1986) for firms have been discussed by a vast group of scholars (Bengtsson and Kock, 1999, 2000; Gnyawali and He, 2006; Gnyawali and Park, 2009; Lado et al., 1997; Pellegrin-Boucher et al., 2013), while some papers focus on plausible positive and negative gains and impacts of coopetition (Bonel and Rocco, 2007; Brandenburger and Nalebuff, 2011; Hamel, 1991; Nieto and Santamaria, 2007; Oxley and Sampson, 2004; Shapiro and Varian, 1999).

2.2.2

Coopetition in ICT

ICT industry has been no exception for scholars for contextualizing coopetition. On one hand, Gnyawali and Park (2009) look into the role of coopetition in achieving technological innovations in Smart and mi-sized enterprises taking examples from ICT industry. Pellegrin-Boucher et al. (2013), using a qualitative approach, investigate the evolution of interfirm coopetitive agreements in the light of stability of coopetition in ICT. Ritala et al. (2008) look into centrality of firms in both competitive and cooperative networks, and discuss its importance in forming coopetitive relationships. On the other hand, cooperation among competitors of the wireless ICT industry has also attracted attentions (Basole, 2009; Gueguen, 2009; Gueguen and Isckia, 2011; Maitland et al., 2002; Peppard and Rylander, 2006; Zhang and Liang, 2011). A viable instance of cooperation among competitors is then formation of strategic alliances in order to impose standards in technology within standardization bodies (Gueguen, 2009; Shapiro and Varian, 1999). Almost all of these discussions follow the aforementioned definition by Bengtsson and Kock (1999) on coopetition that is cooperation with direct competitors. If we consider ICT a knowledge intensive industry, according to Powell and Brantley (1992), in such industries cooperation and competition are common strategies that firms adopt and adapt. One direct indication of intensity of knowledge is the cost of R&D and the knowledge (know-how). Dittrich and Duysters (2007)


19

consider “the pool of common knowledge” as a way of reducing such costs; a direct cooperative system among competing firms. Although when the products are developed based on the common achieved knowledge, networks start to dissolve; firms start to integrate the know-how that was achieved through cooperation to their own organization, and competition rises again and becomes the dominant relationship (Pellegrin-Boucher et al., 2013). Gueguen (2009) sees the after effect of such cooperation and considers “differentiation” as the acquired strategy by firms in order to create entry barriers for competitors once the cooperation starts to dissolve. But still the complexity of market does not limit to cooperation for just one product. There have been many cases that firms cooperate over a specific R&D knowledge, once the knowledge is almost mature start to compete over the product while integrating the knowledge and already cooperate on another know-how for yet another technology, R&D, and know-how (Gueguen, 2009; M’Chirgui, 2005). Our “layered”–onion–approach on contextualizing coopetition for describing relationships in ICT is illustrated in Figure 2.1.

Figure 2.1:

2.2.3

The focus of our literature review on coopetition

Value Networks and Value Creation

The networked structure of businesses in an ecosystem Holm et al. (2015) is based on the premise of “no business is an island” (Håkansson and Snehota, 1989), where firms do not just operate in dyadic relationships (James C. Anderson Håkan Håkansson, 1994), which means firms are heavily involved in complex economic systems that consist of inter-organizational business relationships (Basole and Rouse, 2008). This concept replaces the idea of linear flow of value in chains first introduced by Porter (1985). Value chain consists of dyadic relationships among business entities that starts from raw material providers on one hand and finishes by end users on the other hand. Normann and Ramirez (1993a) argue that value chains

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are inadequate for accommodating complex market structures and business relationships (Bovet and Martha, 2000; Stabell and Fjeldstad, 1998), which means that products and services in complex markets are not any more designed and produced in linear processes. At the same time these services (values) (Narula, 2014) need to be produced/created and delivered to end customers via value networks (Allee, 2000; Brandenburger and Nalebuff, 2011; Kothandaraman and Wilson, 2001). A step further from networks of creating value is also introduced as value grids (Pil and Holweg, 2006) and value webs (Kelly and Marchese, 2015). Characteristics of these networks, such as size, relationships among actors, number of existing and possible ties, connectedness, centrality, and control, are often considered vital to describing the structure of the networks (Anderson and Narus, 1991; Pfeffer and Salancik, 2003; Ritter et al., 2004). At the same time, the role of services in formation of value networks and the emergence of concepts such as product, servitization, and service dominant logic is an important angle on this topic.

2.2.4

Value Networks and Services

In the process of product servitization there is a long tradition of analyzing production, creation, and consumption of both products and services (Fisk et al., 1993; Shostack, 1977; Zeithaml et al., 1985). Differentiating between products and services has also gained attention (Vargo and Lusch, 2004; Zeithaml et al., 1985), although servitization roots back in 1972 and Levit’s description here he believes “everything is a service” (Levitt, 1972). According to Araujo and Spring (2006), if we consider products as “vehicles for service delivery”, we can argue to bridge the gap between products and services and consider networks (Casti, 1995) as the place where products and services are created, delivered, and consumed. If we define value as a measure of the benefit provided by a good or service to an actor, we can better understand the concept of value networks and how services relate to this network. Kothandaraman and Wilson (2001) argue that the creation of value is also influenced by the transformation from value chains to value networks (Möller and Wilson, 1995; Parolini, 1999). This means that the value is created at the network level (Basole and Rouse, 2008; Bovet and Martha, 2000), rather than the relational level. It should be added that, according to Vargo and Lusch (2004), we consider the customers also as the co-creator of value. Hence, each actor who participates in the network is supposed to incrementally contribute value to the overall offering (Bovet and Martha, 2000).

2.2.5

Value Co-Creation

The concept of co-creation and respectively co-creation of value has attracted diverse attention in variety of research fields. The process of creating value, traditionally, has been seen as an individual quality. More recently, in the light of emergence of value networks and by examining the process of creating value in-depth, the actual situation makes it clear that the original hypothesis has been invalid for long.


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Hence the literature argues that the value is co-created. We adopt the definition of co-creation by Tokoro (2015) where he considers Co-creation as “a practice of creating value through cooperation among multiple active agents with certain shared purposes that agents acting in isolation cannot achieve”. We use this definition to further describe the process of creating value in the future telecom value networks and discuss the importance of value creation in interfirm relationships. A closely related field to co-creation, which is also considered as the reasoning for value co-creation is the Service-Dominant Logic (S-D logic), proposed by Vargo and Lusch (2004). S-D logic in the area of service marketing considers customers as the major co-creator of value together with the service provider, where Tokoro (2015) believes that the participation of customer is greatly changing the concept of services. We argue that the major consequence of this cooperation over value cocreation is the change from traditional products that are based on prices to services replacing products and the idea of everything as a service (XaaS). The S-D logic and the co-creation value have raised the attention towards analyzing the process of value creation in different research fields and industries. The research on this topic mainly focuses on the “process” of co-creating value based on interfirm relationships in the B2B context (Echeverri and Skålén, 2011; Grönroos and Voima, 2013; Gummerus, 2013; Gummesson et al., 2010; Payne et al., 2008; Saarijärvi, 2012; Vargo et al., 2008).

2.2.6

Wireless ICT Value Networks

The ICT industry–and specifically the wireless ICT–is no exception to process of shifting from value chains to value networks (Funk, 2009; Li and Whalley, 2002; Peppard and Rylander, 2006). Discussions on transformation of wireless ICT from value chains to value networks (Li and Whalley, 2002) generally examine the underlying reasons for such a disruptive change and identify various types of actors who are involved in such value networks. Although wireless ICT firms, like any firm in other industries, are independent in the value network (Peppard and Rylander, 2006), they enjoy inter-firm relationships in the network (Jarillo, 1988) that are essential to their competitive positions. These relationships are reasons for evolving industries and are quite important to boost the performance (Madhavan et al., 1998) of the firms in wireless ICT value network. Besides the mentioned contributions on the formation of value networks in Wireless ICT, a series of literature exist on this matter (Basole, 2009; Kuo and Yu, 2006; Olla and Patel, 2002; Sabat, 2002). Maitland et al. (2002) describe the key factors that will shape the transition towards next generations of telecommunications technology and challenges faced by main actors from the evolving value chains perspective. Funk (2009), in return, considers how the telecom industry is changing from value chain to a value networks, focusing on UEs as the unit of analysis. At the same time, Ballon (2007) looks into the design of business models in accordance to the creation of value within the system.

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Our layered approach on creation of value in forms of value networks for the wireless ICT industry is illustrated in Figure 2.2.

Figure 2.2:

2.3

The focus of our literature review on value creation

Where is The Research Gap?

Looking into the previous section, we have conducted our literature review on the three main areas: • Competition and cooperation areas, presented in section 1.3.1 • Coopetition, contextualizing coopetition, and coopetition in ICT • Value networks, services in value networks, value co-creation, and value networks in ICT Now, if we put together the latter two bullets, and overlap the presented literature review, it will enable us to discuss “value networks in ICT” in the presence of “coopetition in ICT”. In the previous section, on one hand we have presented the literature on “Coopetition in ICT” (Figure 2.1), and on the other hand we have discussed the literature on “value networks in Wireless ICT” (Figure 2.2). Now we put together these two figures and shows the overlapped area in Figure 2.3, which illustrates what would happen if we expand “value network in ICT” to the other area and try to discuss it based on “coopetition in ICT”. This way, the presented figure shows where coopetition can be used in order to describe the business relationships among firms in value networks for the future telecom industry.

2.3. WHERE IS THE RESEARCH GAP?

Figure 2.3:

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Describing relationships by coopetition theory in the value networks of ICT

Based on presented literature, the business relationships and transactions among firms in any ecosystem is considered as the major basis for value co-creation. This means that it is the interfirm relationships for co-creating value that is the main cause for formation of value networks. These B2B transactions basically consist of competition and cooperation, and the more complex instances then comprise simultaneous competition and cooperation among firms within business networks; the so-called coopetition. At the same time, when it comes to contextualizing coopetition, the most commonly used definition of coopetition is the one presented by Bengtsson and Kock (1999) that considers coopetition as the cooperation among competing firms. But, as we have discussed before, based on the literature on value creation and specifically formation of value networks, simultaneous cooperation and competition relationships do not limit to just cooperation among competing firms. The complexities of relations go beyond this and in many instances to competition among firms who are already cooperating with each other.

Figure 2.4:

The research gap illustrated by the hatched area

24


Now the question is what would happen if we put coopetition as a tool for describing relationships in the value network of wireless ICT into the context of machine to machine communications as an enabler for smart city. This question, which is the identified research gap is then simplified and illustrated in Figure 2.4 by the hatched area between “Value networks in ICT” and “Coopetition in ICT”. As a result, in the coming chapter 3 we will describe the problem that is derived from the gap that will be used as the research problem introduced by this thesis and formulate our research questions based on the problem.

Chapter 3

Problem Description 3.1

Value Co-Creation in Light of Coopetition

Considering ICT as the transformation tool for other industries, 5G–as a component of future telecom industry–can be the supporting force from the Wireless ICT for enabling communications requirement. This transformation tool is then heavily dependent on co-creation1 of value together with the target industries rather than creating value in form of linear chains and passing products to next actor in the chain. This results to formation of value networks that replace value chains. The need for telecom value network is highlighted when this industry is entering new markets and telecom is supposed to serve as a tool and not the final product. Narrowing down the scope of transforming industries to Smart City context, Smart City comprises inter-related industry verticals, which create a complex ecosystem. Considering the role of traditional telecom actors in smart city context, the need to co-create values, both internally (between telecom actors) and externally (between telecom actors and non-telecom actors), is obvious. It should not be forgotten that traditional telecom actors (i.e. MNOs and TEVs) have long been doing their business inside the telecom value chain and are used to linear value creation, cooperating with their own telecom supplier-customers (Figure 1.1). Besides MNOs and TEVs, a new set of actors also participate in the co-creation of value in the new telecom value network. This new entrant is the entity that utilizes the telecom-enablement and offers telecom-enabled services. As a result, the first problem is how would traditional telecom actors adopt value co-creation and adapt value networks instead of value chains. In the context of Smart City the new entrant to the telecom value network is in most cases the Service Providers (SP) of the non-telecom industries. If we consider the telecom ecosystem in smart city comprising traditional telecom actors and these new players, co-creation of value then boils down to cooperation/collaboration among all these three groups of actors. At the same time, competition is 1 Value

co-creation is discussed more in details in chapter four.

25

26

CHAPTER 3. PROBLEM DESCRIPTION

also quite fierce among these actors for many reasons such as more sales/revenue (between identical firms), controlling the ecosystem, and even major changes in the market (between non-identical firms) that cause new competition behaviors such as competing with direct cooperators. If we consider the simultaneous cooperation and competition as coopetition; one can argue why is the focus of this thesis on competition with cooperators and not vice versa? The answer is that at inter-organizational level, firms cooperate with each other in order to reach a higher level in creating value compared to what they can reach if they do it alone. This justifies the cause of cooperation and co-creation of value. Therefore it is quite vivid why two or more competing firms tend to cooperate even though they have been involved in rivalry situation for some time; although analyzing this situation requires exhaustive research. At the same time, what seems to be a higher risk for firms is to start competition with another firm which they have cooperation relationships in place. This way the risks of damaging the “good” relationships are quite high; and the question is whether the firms can afford such damages or not. Regarding cooperation, MNOs are used to cooperating with competitors. As an instance, MNOs in different markets have been cooperating with each other mainly in order to cut costs, as well as dealing with lack of resources. But competing with cooperators is not common. An example can be TEVs competing with their customers (e.g. MNOs) over a new service to be offered to a Smart City vertical. The question is then what are the drivers for such competition? At the same time, if a firm wants to compete with its cooperators, it needs to see the risks and it is important to understand what is at stake if it competes with its cooperator (e.g. its customer or supplier). Another question to be answered is what are the risks and uncertainties involved in competing with cooperators? Therefore, the second problem relates to the way that firms interact with each other in the new value network. From MNOs’ perspective the situation regarding the described problem is as follows. The business model of MNOs corresponds to vertical solutions, and they are not used to value networks, instead used to value chains. This would mean that where to position in value network is also a question for them. Threat of new entrants that can take over MNO’s primary role in a new market is a major issue, while they need to compete with suppliers and customers in value networks and cooperate with them at the same time. Co-creation of value with other industries is new for MNOs, although they have been cooperating with their (almost) identical competitors for cost-cut and/or due to lack of resources for some years. MNOs are used to B2C offerings and services in mobile telephony value chain, while they need to offer B2B services in SC context. From TEVs’ perspective, the situation is the following. The business model of TEVs also corresponds to vertical solutions in traditional telecom value chains. Instead, they are familiar with value networks and have a better understanding of co-creation of value with other business customers, since they have played the role of suppliers for other industries as well. This means that TEVs also are not

3.2. DISCUSSION ON RESEARCH QUESTIONS

27

used to offer services to end users of a value network, because they mainly acted as suppliers. TEVs are not used to cooperating with competitors and competing with cooperators (e.g. customers like MNOs). And their customers used to be big firms, now offering services to smaller SPs. From SPs’ perspective, the situation is as follows. Whether we differentiate between small OTT SPs or other industry actors as SPs, when it comes to provisioning mobile services, they very much depend on other actors of the telecom value network. This is mainly due to the lack of resources and competences. In case of small SPs, they need to spot empty roles in the value network and fill the holes in order to be profitable. And finally, SPs should be able to handle end users since they may become an interaction point with end users.

3.2

Discussion on Research Questions

In this section we discuss the introduced research questions from section 1.3.3. The main idea is to discuss the questions and show how they can help this study overcome the introduced problem of the thesis. The main question of this thesis is to clarify where is the competition and cooperation in future mobile service provisioning? Since the above statement and question is not easy to resolve, it should be elaborated: RQ1 : Why do competitors in mobile service provisioning have to cooperate? The first question deals with the reasoning of cooperation among actors in the wireless ICT ecosystem. Considering cooperation as the key to success, we believe that there are various reasons that, to some extent, forces the actors of “future telecom” ecosystem to cooperate with each other. This question also helps us to look into how is that possible to cooperate while a competitive nature is dominant over the relationships of two firms. On the other hand, by the aid of this question we would like to see whether there is a need for firms to collaborate on creating services/products, or solutions can be vertically integrated by the actors. The cooperation can occur or arise as a natural consequence of changes but also can be an initiator of changes. We would tackle this question from three different perspectives; the unit of cooperation, the reason for cooperation, and the consequences of cooperation. RQ2 : Why do cooperators in mobile service provisioning compete? In the second question we will try to find out reasons for “jeopardizing” existing relationships that are “good” enough that already created cooperation among firms. We would like to see what the drivers are and whether they are tempting enough to convince firms to risk their cooperative relationships and compete. We will also look into what happens when competition happens and if it causes any considerable

28


change to the ecosystem. In our cases we also check “where” such competitions are more likely to happen. RQ3 : How would repositioning in the telecom value chain benefit traditional actors2 of telecommunication industry? Eventually, the third question investigates the consequences of cooperation and competition in future telecom ecosystem, in light of the value creation process. For this matter we look into strategies that traditional wireless ICT actors would adopt while they enter new markets and perform new businesses. The new markets refer to the ones that ICT acts as a tool and enabler rather than the end product. Hence, the businesses might not be completely new but the market could be completely different compared to their “home turf” that is mobile telephony. We will investigate whether these actors would leave the value creation process, adapt and change their business, or be replaced by others.

3.3

Contributions

This section defines how we will tackle the research questions in this thesis. In the first part of this section we present the work we have done, according to our 17 published peer reviewed papers that are related to this thesis. We mainly highlight the key ideas of each paper and mention how the contribution to each paper is relevant to this thesis. Among these 17 we handpick 5 papers that more specifically embody the cases and analyses introduced in this thesis and append them at the end of the thesis. The appended papers are: 1–12–15–16–17 from the upcoming list of papers. Next, in the second part of this section, we discuss the contribution of this thesis in specific. The contribution then directly helps answering the research questions.

3.3.1

Publication Contributions

On Network Sharing 1. “Shared Smallcell Networks Multi–operator or Third party solutions -or both?”, 11th International Symposium on Modeling & Optimization in Mobile, Ad Hoc & Wireless Networks (WiOpt) - Workshops (WiOpt - IOSC), Tsubaka, Japan, May 2013 Jan Markendahl, Amirhossein Ghanbari 2. “Study on Effect of Backhaul Solution on Indoor Mobile Deployment -Macrocell vs. Femtocell”, 24th IEEE Annual International Symposium on Personal, 2 Traditional actors of telecommunication industry, in this thesis, refer to Mobile Network Operators and Telecom Equipment Vendors.

3.3. CONTRIBUTIONS

29

Indoor, and Mobile Radio Communications (IEEE PIMRC), London, UK, September 2013 Ashraf Ahmed, Jan Markendahl, Cicek Cavdar, Amirhossein Ghanbari 3. “Toward Capacity Efficient, Cost Efficient and Power Efficient Deployment Strategy for Indoor Mobile Broadband”, 24th European Regional International Telecommunication Society conference, Florence, Italy, October 2013 Ashraf Ahmed, Jan Markendahl, Amirhossein Ghanbari 4. “Network Cooperation between Mobile Operators -Why and how competitors cooperate?”, 29th International Marketing and Purchasing group Conference, Atlanta, USA, August 2013 Jan Markendahl, Amirhossein Ghanbari 5. “Cooperation patterns in small cell networks -Risks and opportunities to distinguish the win–win model”, 24th European Regional International Telecommunication Society conference, Florence, Italy, October 2013 Amirhossein Ghanbari, Jan Markendahl 6. “Regulations for and against Cooperation in smallcells -How could regulations stimulate co–opetition by supporting sharing?”, 24th European Regional ITS Conference, Florence, Italy, October 2013 Amirhossein Ghanbari, Jan Markendahl, Ashraf Awadelakrim Widaa 7. “Complementing macrocell deficits with either smallcells or Wi-Fi -Willingness to choose based on the cost-capacity analysis”, 24th European Regional Regional International Telecommunication Society conference, Florence, Italy, October 2013 Razvan Popescu, Amirhossein Ghanbari, Jan Markendahl The papers presented here contain a unified contribution that is built in a series of publications; meaning that the papers are complementary to each other and there is minor overlap in these papers. In paper 1, 2 and 3, we have discussed different possible solutions for indoor deployments. Various possible actors have been taken into considerations (e.g. MNOs and non MNO network operators); where in latter technical issues on deployment (e.g. backhauling) are more focused. In this collection I have contributed by describing possible indoor network deployment solutions, indoor network sharing strategies and the role of trusted third party actors. In paper 4 we have focused on cooperation among MNOs and discussed how and why competitors cooperate in indoor cellular networks. In paper 5 we have tried to present a win-win model for traditional and emerging actors of indoor network deployment. This means that the business related risks and opportunities have been identified and analyzed. Paper 6 then complements the previous paper by studying the regulations on network sharing proposed by national regulatory authorities. Eventually, in paper 7 we have considered Wi-Fi as a competing solution for indoor cellular deployments that is believed to pave the way for future works. In this

30


collection I have contributed by looking into the business relationships among actors of the indoor cellular network ecosystem. I have contributed by identifying the risks and uncertainties of cooperation among existing actors and discussed the presence of new entrants. The formation of value networks for indoor cellular networks in case of sharing networks is also presented. On Machine to Machine Communications 8. “Internet of Things: Redefinition of Business Models for the next generation of Telecom services”, 26th European Regional International Telecommunication Society conference, San Lorenzo de El Escorial, Spain, 2015 Amirhossein Ghanbari, Óscar Álvarez, Jan Markendahl 9. “Migration Strategies in Network Deployment to Support M2M Communications”, 6th annual CMI conference, Aalborg University Copenhagen, November 2013 Andrés Laya, Amirhossein Ghanbari, Ashraf Ahmed, Jan Markendahl 10. “Smart Energy: Competitive Landscape and Collaborative Business Models”, 18th International Conference on Intelligence in Next Generation, Paris, France, February 2015 Óscar Álvarez, Amirhossein Ghanbari, Jan Markendahl 11. “Analysis of regulatory, market and cost structure aspects for deployment of private or shared Mobile networks for high quality M2M communications”, 25th European Regional Regional International Telecommunication Society conference, Brussels, June 2014 Jan Markendahl, Amirhossein Ghanbari, Mårten Sundquist 12. “Tele–Economics in MTC: what numbers would not show”, EAI Endorsed Transactions on Internet of Things, vol. 1, pp. 1–12, October 2015 Andrés Laya, Amirhossein Ghanbari, Jan Markendahl In Paper 8 we provide an assessment of existing M2M business models and arrangements in selected industry segments. We studied the drivers and barriers for adaption of M2M and IoT in transforming operations in the selected industry segments, and focus on identifying recurring patterns in the transformation process. In this paper, I discuss the change in value propositions as well as how value networks transform from the telecommunication market perspective. Paper 9 focuses on strategies how cellular networks should migrate to networks that support M2M communications. Looking at this migration from MNOs’ perspective, the paper identifies the role of MNOs in this shift. By focusing on the case study of Utility sector, papers 10 generates and understanding for the smart grid deployments in different countries and the importance of communications in this context; This is done by tracking market trends for development of ICT based mM2M. The papers also discuss communications of smart grid more in details from

3.3. CONTRIBUTIONS

31

a Telco Vendor’s perspective while analyzing different business opportunities and possibilities. As a result, paper 11 introduces three different options of cellular networks for provisioning mM2M (Utility sectors is used as case study). The paper discusses these three options in terms of costs and gives insights on network deployment for traditional MNOs, Utility companies, and emerging M2M network providers. Paper 12 elaborates the relevance of conducting Techno–economic research on Telecommunications in order to understand the effect that MTC has on different industries. The paper also discusses the adoption of services based on M2M and MTC. We argue the concept of service and the emergence of services substituting products from the perspective of change in the telecom industry’s mind–set where I present the ideology of co–creating value in telecom industry and transition from value chains to value networks for wireless ICT. I also discuss the road towards 5G in this paper from the perspective of utilizing 5G as a tool for transforming other industries. On Smart City 13. “Horizontalization of Internet of Things services for Smart Cities -Use cases study”, International Conference on City Sciences, Shanghai, China, June 2015 Óscar Álvarez, Amirhossein Ghanbari, Jan Markendahl 14. “Coopetition in M2M ecosystem -the case of smart cities“, IEEE International Conference on Sensing, Communication and Networking (IEEE SECON)Workshop on “Smart Wireless Access Networks for Smart City”, Seattle, USA, June 2015 Amirhossein Ghanbari, Óscar Álvarez, Jan Markendahl 15. “Repositioning in Value Chain for Smart City Ecosystems -a Viable Strategy for Historical Telecom Actors”, American Regional International Telecommunication Society conference, Los Angeles, USA, October 2015 Amirhossein Ghanbari, Óscar Álvarez, Thomas Casey, Jan Markendahl 16. “MTC Value Network for Smart City Ecosystems”, IEEE Wireless Communications and Networking Conference (IEEE WCNC) - Workshop on “5G Enablers & Applications”, Doha, Qatar, April 2016 Amirhossein Ghanbari, Óscar Álvarez, Jan Markendahl 17. ”Value Creation and Coopetition in M2M Ecosystem - The Case of Smart City”, 27th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (IEEE PIMRC) - Workshop on “From M2M Communications to Internet of Things”, Valencia, Spain, September 2016 Amirhossein Ghanbari, Andrés Laya, Jan Markendahl

32


Looking into generic foundation of Smart city and its building blocks discussed earlier; in paper 13 we focus on different Smart City use cases in four sectors; public transportation services, automotive and vehicle related services, smart energy services, and health care and home care services. In this paper I discuss how ICT transforms industries and how ICT plays an important role in all various industries of future. The paper also discusses how ICT solutions in different coexisting verticals are offered in forms of individual Silos. Avoiding interoperability, lack of cooperation with other service providers, and vertically integrated business models are also surveyed and discussed in these papers. The main conclusion of these articles represent that there is a need for change in the business model of involved actors. This paper is complemented by paper 15. Paper 14 dives deeper into the Smart City concept by discussing relationships among telecom actors in this context. The paper identifies main telecom oriented activities, resources, and actors (ARA) in the Smart City context, and tries to introduce basic relations among different actors. In this paper I have contributed by introducing the ARA framework and identifying the involved activities and their related resources. This paper is complemented by paper 16. In paper 15 we elaborate on paper 13 and complement its results by discussing repositioning of traditional telecom actors in telecom value chain. We propose this strategy as a viable tactic for future telecom actors in order to sustain their revenues in this industry. We use Smart Cities as a new market for Telecom industry, where instances of future telecom can be seen. In this paper I mainly discuss the relevance of some major resources involved in provisioning telecom services. I also discuss the irrelevance of linear value chains in the sense of provisioning ICT services in new markets and identify possible repositioning schemes for telecom actors. Paper 16 elaborates on findings of paper 14 and argues smart city as a good opportunity for traditional actors of telecommunication industry who are looking for new markets and revenue streams. The paper introduces a new mindset for these actors to re-positioning themselves in the Smart City value chain. This means that, in order to play a role that cannot be overlooked, they should perform rather different blocks of the Smart City value chain compared to their traditional activity blocks in Mobile Telephony value chain. This paper highlights the role of MTC for enabling Smart Cities and presents four smart city use cases that are enabled by MTC/M2M. An abstract M2M/MTC activity framework is presented in this paper that is followed by the abstract M2M/MTC value network. In Paper 17 we discuss the process of creating value in the future telecom value networks, when ICT merges with other industries. We argue the co-creation of value among telecom actors and actors from other industries who take part in the value network, while considering connectivity as an enabler for other industries. In this paper we discuss that linear telecom value chains are incapable of serving this new demand and the fact that this chain would cause the formation of telecom value networks. As a result the paper presents Cooperation with competitors and Competition with cooperators as two instances of emerging business relationships where traditional telecom actors have to implement.

3.3. CONTRIBUTIONS

3.3.2

33

Thesis Contribution

Since this thesis is a “Compilation thesis”, the accumulation of the papers’ contribution would form the thesis contribution. The contribution then directly provides insights for answering the research questions introduced earlier, as well as concluding the thesis. As a result, the contribution of this thesis would eventually show “where the coopetition is in future wireless ICT ecosystem”, while highlighting the difference between horizontal and vertical coopetition in this context. The thesis’ contribution is illustrated in more details in Figure 3.1. In section 4.2 we will describe the bottom part of the figure in details, and discuss how theories will be used in order to reach the contribution. We clarify the thesis’ contribution as four major proposals that will be later on discussed in different chapters:

Figure 3.1:

What to show in this thesis, and how to show it.

34


MTC Activity Framework We introduce a framework to study MTC activities for provisioning M2M/MTCenabled services. The framework illustrates the relations among activities in terms of interdependencies, as well as the sequence of activities to be performed. The main idea behind implementing this framework is to present the value flow. This framework will eventually facilitate the process of distributing responsibilities among actors and also helps identifying the actors and possible grouping of activities to be performed by each actor. This contribution is discussed in details in section 6.3.1. MTC Value Network We propose an abstract Value Network for MTC-based mobile service provisioning. The abstraction is on the firm level that means any actor who owns the resources-competences associated to each activity can perform the activity. Based on this value network, it can be identified what are the business relationships that will happen in case any actor choose to perform a set of activities from the activity framework. This contribution is discussed in details in section 6.3.3. Coopetition Points in Future Wireless ICT We propose the coopetition points in terms of competing with cooperators in the Wireless ICT industry where the future telecom acts as an enabler for other industries. The coopetition points show where cooperating firms could compete with each other in this ecosystem when it comes to new business setups, specifically new markets for future telecom. This contribution is discussed in details in section 7.2. Vertical Coopetition As the major contribution of this thesis, we introduce and propose “vertical coopetition” as a critical business relationship in value networks for the future telecom industry. Vertical coopetition highlights the importance of possible competition among firms that already have cooperative relationships in place. We differentiate and compare the two angles of coopetitive business relationships. These two types of relationships can be used for describing business interactions among firms in the wireless ICT ecosystem. The first angle is horizontal coopetition, which comprise cooperation among competitors. This angle is less complicated and better known. The second angle, which is the focus of this thesis, then embodies competition among cooperators. This has been less discussed by the scholars (please refer to section 2.2). By introducing vertical coopetition we draw the attention to the fact that what would happen if cooperating firms start to compete. First we resolve the uncertainties related to the fact that whether vertical coopetition affects the formation of value creation processes. Hence we introduce the effect of vertical coopetition on the value creation process for wireless ICT ecosystem, and present how it possibly changes the business relationships among firms in networks. In this regard, we also discuss the position of firms in aforementioned value networks. On the other

3.3. CONTRIBUTIONS

35

hand, we introduce the risks associated with entering competitive relationships for cooperating firms. We discuss if it affects the existing relationships among firms and elaborate on whether firms stay in cooperation after they start competing. In this regard we propose two sets of drivers for staying in cooperation: Financial and Relational. This contribution is discussed in details in section 7.3.

Chapter 4

Methodology and Theoretical Foundation 4.1

Methodology

The general field of study in this thesis is an interdisciplinary research on Telecommunications’ microeconomics. The main idea is to make it possible to achieve breakthroughs (Fleming, 2004) by mixing two disciplines that are unlikely to be mixed by academic scholars. The study analyzes the telecommunication industry’s business behavior in terms of inter firm relationships. This is a step in attempt to understand the decision-making process of firms. As a result, our Techno–economic research is concerned with the interaction between individual service providers and business customers and the factors that influence the choices made by them. Hence, the main setup then is Business to Business (B2B) relationships. To perform this thesis work, given the explorative nature of the research objectives, a qualitative research method is chosen. The aim is to gain an understanding of underlying reasons and motivations regarding the stated problem in previous chapter. We follow a general method proposed by Håkansson (2013) to follow step by steps illustrated in Figure 4.1. Eventually, we aim to uncover prevalent trends in thoughts and opinions regarding the research gap (section 2.3) from major actors’ point of view.

Figure 4.1:

Qualitative research steps in this thesis

37

38

CHAPTER 4. METHODOLOGY AND THEORETICAL FOUNDATION

4.1.1

Research Approach

The Research approach chosen is Inductive approach (Bryman and Bell, 2015; Salkind and Rainwater, 2003; Trochim and Donnelly, 2001) (i.e. reasoning), which formulates theories and propositions with alternative explanations from observations and patterns. Data is collected, commonly with qualitative methods, and analyzed to gain an understanding of phenomenon and establishing different views of the phenomenon. The outcome is based on behaviors, opinions, and experiences and must contain enough data to establish why something is happening, which are the reasons for the theories or requirements for an artifact.

4.1.2

Research Strategy

For the research strategy Exploratory Research method is chosen that provides a basis for general findings by exploring the possibility to obtain as many relationships between different variables as possible (Shields and Rangarajan, 2013). It rarely provides definite answers to specific issues. Instead, it identifies key issues and variables to define objectives, using qualitative data collection.

4.1.3

Data Collection

For collecting data, we will use literature study and Case Study. The former consists of studying secondary data such as reports, conference presentations, brochures, online information, user guides, press releases, white papers, articles, and other documents as such. The latter (Case Study) is an in-depth analysis of a single or small number of participants. To complement data collection, unstructured or semi-structured data collection techniques i.e., group discussions with industries and researchers and individual interviews are also performed. This field research consists of a set of case studies; among them four have been chosen and presented in this document (described in section 6.2). A set of interviews has been performed with managers, business modelers and technicians from different actors’ sides during “Johannesberg Summit 2016”, and as part of preparation for projects. The group discussions include: 1. Participating in “Strategic Innovation Agenda for Smart Sustainable Cities”, which is an initiative by KTH Royal Institute of Technology. 2. Participating in projects (Table 4.1) within the following programs/frameworks: Horizon 20201 , Vinnova2 , EIT Digital3 , and Wireless@kth4 seed projects . 1 The

EU Framework Programme for Research and Innovation. Innovation agency. 3 European digital innovation and entrepreneurial education organization. 4 Vinnova Industry Excellence Center. 2 Swedish

4.1. METHODOLOGY

39 Table 4.1: Participated projects

Project

Year

M2M gap

2013 2014

M2MRISE

Partners

Main Objective

Financier Wireless @KTH

KTH

To identify research gaps in both the technology and,technoeconomical domains.

2014

Orange, Aalto U, Ericsson, Nokia

To link technical requirements, services and applications and, adequate business models for large scale M2M deployments.

LTE4SE

2014

Siemens, Ericsson, KTH

To evaluate and demonstrate how LTE technologies can enable Smart Grid,applications, from monitoring to real time control.

KANTiL

2014

MSB, Skogforsk, SCA, Net1, Cloudberry, Wireless@kth

To build a constellation of partners and develop mature ideas on how to enable improved connectivity in remote, and rural areas.

Vinnova

ICT transformation

2014

Ericsson, Stockholm School of Economics, KTH

Running parallel M.Sc. theses, in order to look into possible use cases that ICT can transform other industries.

Ericsson

EXAM

2015

Aalto U, Telecom Italia, Acreo, KTH, Ericsson, Lund U

To provide solutions for Cellular access to networks, while suggesting energy efficient communications

METIS II

2015 2016

23 partners: MNOs, TEVs, SPs, Universities, Research centers

To develop the overall 5G radio access network design and to provide technical enablers needed for an efficient integration and use of the various 5G technologies and components.

H2020

IoT Ecosystems

2016

Sandvik, Almega, KTH, Biosync, Ericsson, Stockholms Kommun, TeliaSonera, Vattenfall

To study different industries and their ecosystem and identify opportunities and issues related to IoT.

Vinnova

EIT Digital

EIT Digital

EIT Digital

40

CHAPTER 4. METHODOLOGY AND THEORETICAL FOUNDATION 3. Participating in applications (Table 4.2) for projects within mentioned programs/frameworks in item number 2. Table 4.2: Participated applications for projects Project

Year

Partners

Main objective

FLOWER

2014

Alcatel-Lucent, Huawei (FI), Huawei (SE), Hellenic Telecommunications Organization S.A. , KTH, Swedish Post and Telecom Authority, Netherlands Organisation for Applied Scientific Research, WINGS ICT Solutions Ltd.

Flexible and Secure Coopetition for Wireless Network Sharing

H2020

Financier

KANTiL phase II

2015

Refer to KANTiL project in table 4.1

Continuation of KANTiL project from table 4.1

Vinnova

PERFECT 2015

Ericsson, KTH, VTT Finland, ABB Finland, ABB Sweden, ITS Lab Italy, Sielte Italy, CEA France

Proactive Emergency Response based on Flexible and Enhanced Communication Technologies

H2020

4. Attendance to Conferences and Workshops, including a) IEEE Communication Society conferences and workshops such as IEEE PIMRC, WCNC, WiOpt, and SECON. b) International Telecommunication Society conferences. c) International Marketing and Purchasing group conference. d) Summits such as Johannesberg Summit. and d) Research workshops the RS Lab group in Communication Systems department, KTH University.

4.1.4

Data Analysis

For analyzing data Analytic Induction and Grounded Theory methods will be used (Håkansson, 2013). These two are iterative methods that alternate between collections and analyses. The iterations continue until no cases dismiss the hypothesis or theory. Analytic induction stops when the hypothesis and grounded theory ends with a validated theory. We will use three specific theories for this part that are ARA, Porter’s five forces, and Coopetition. These theories would allow us to conduct content analysis of collected data and studied literature in order to understand the context of the actors’ decisions, intention and opinion. On the other hand, empirical data analysis will be mainly used in order to perceive the current situation in the market and major drawback of implementing a coopetitive system. Since

4.2. THEORETICAL FOUNDATION

41

these three theories are broad and cover many aspects, we will limit them to the scope of this thesis and use specific parts of them for our research. This is discussed in details in the next section.

4.2

Theoretical Foundation

In this section we will discuss the three main theories namely ARA, Porter’s Five Forces, and Coopetition. We will discuss how we adopted these theories, and in two cases how we modified them in order to fit our analyzes. These theories, according to the contribution section, are used in this thesis for the sake of performing analyzes. First we look into where these theories are being used.

Figure 4.2:

Where theories are applied in the thesis

The bottom part of Figure 3.1 illustrated how coopetition will be shown in this thesis. Figure 4.2 expands this part by showing where the mentioned theories are applied in different steps of the study. According to Figure 4.2, in order to show coopetition points in future telecom, we will start by studying the market based on collected data. Thereafter we propose a framework for studying the activities in the process of creating value. Next, in order to identify relationships in the network we use the ARA model. Based on identified relationships we propose an abstract value network. Next, we identify possible roles for any focal firm according to proposed value network and based on the prior ARA analysis (specifically

42


Resources-Competences). We will then use P5F as a checklist for finding out competitors as well as cooperators while considering the entire network. Eventually we will define competition and cooperation points and discuss them based on coopetition model. It should be highlighted that in this thesis we do not directly use the coopetition theory as presented by Bengtsson and Kock (1999) for analysis. Instead we derive and present a different model of coopetition in the wireless ICT ecosystem in section 7.3.3, which is called “vertical coopetition”. We do this based on our analyzes by mixing the former two theories; ARA and P5F. However, in the last part of this section, we discuss the original coopetition theory (Bengtsson and Kock, 1999) and show how it is possible to modify this model, in order to study the other angle of coopetition i.e., vertical coopetition; which has been considered quite less by scholars (please refer to related works in section 2.2).

4.2.1

Actors–Resources–Activities

The Actors–Resources–Activities (ARA) model was first introduced in 1992 (Håkansson and Johanson, 1992) in the International Marketing and Purchasing group5 (IMP) research stream. One major focus of the IMP research stream is “a research tradition of empirically based studies of how companies are doing business and of what is created when businesses and other organizations interact”. In this sense the ARA model, as one of the main tools used in this focus of IMP, fits this thesis quite well. The IMP tradition strongly emphasizes the importance of interactions and relationships and considers that business networks develop on this foundation (Wilson et al., 2010). As a result, one aim of the ARA model is to describe business relationships among firms. It is believed that ARA was born out of dissatisfaction with the way business relationships were examined in B2B literature (Håkansson, 2009).

Figure 4.3:

The original logic of ARA (based on Håkansson and Johanson (1992))

The ARA model, based on empirical studies, provides a conceptual framework of the process and outcomes of business interactions. The model suggests the idea that 5 http://www.impgroup.org/about.php


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outcomes of an interaction process (or the content of a business relationship) can be described in terms of the three layers: Actor Bonds, Activity Links and Resource Ties between the counterparts (Figure 4.3) (Håkansson and Snehota, 1995). The model also suggests an inter-connection between these layers, which is affected by the constellation of resources, pattern of activities and web of actors in the wider network (Ford et al., 2008a). The ARA-model should “be seen as a basic model trying to give a picture of the main components of how single business relationships are related to the larger business network” (Håkansson, 2009). For describing the business network/value network by applying ARA, traditionally, it had to be clear who are the actors, what are their activities, and with which resources they perform these activities (Lenney and Easton, 2009) . One major critique on ARA model then is the scarcity of empirical applications of this method (Harrison and Prenkert, 2009; Lenney and Easton, 2009), which may suggest that the model is difficult (the way it is commonly used) to test in empirical studies (Håkansson, 2009). In order to describe the business network/value network we will adopt ARA in this thesis. The importance of the relationships and how these three layers contribute to create the value network is the main reason that we adopt ARA for analysis. According to the contribution section of the thesis, in this work we first identify the M2M activities in the context of Smart City, then identify the resources associated with these activities, and then identify a set of abstract actors that can perform those activities. We will use ARA directly to create the abstract actor list based on the other two levels. Then we use ARA to create the value network based on relationships between actors. This argument then defines how we modify the traditional way that ARA is used in order to fit the cause of using the model here.

4.2.2

Porter’s Five Forces Framework

Porter’s Five Forces (P5F) framework is originally developed by Harvard Business School’s Michael E. Porter in 1979. The framework looks at five specific factors that make a qualitative evaluation of a firm’s strategic position, based on other firms in the industry (Porter, 2008b). In this model the assumption (and the central core) is that firms use bargaining power, entry barriers, rivalry and reduction of the threat of substitutes to maximize their own profit, therefore the model is built on the assumption that power leads to higher profits (and better firms). Although this contradicts our core message that is cooperation among firms, but it highlights competitive behaviors of the firms in the market. Since a major part of our discussions in this thesis focus on vertical competition among firms, we need a theory that is built on the basis of competition for better understanding the decisions/behaviors. We should not forget that the position of the firm in the value network is based on both competition and cooperation business interactions, therefore P5F serves the purpose of our discussion regarding competitive behavior of firms. Hence, we briefly use P5F framework for analyzing the market (from a competition perspective) and mainly use this model for identifying business relationships. The framework looks

44


at five specific factors that make a qualitative evaluation of a firm’s strategic position, based on other firms in the industry. Hence, we use this framework as a checklist to identify important business relationships that the focal firm has while considering competition and cooperation with other firms in the industry/market.

Figure 4.4:

The Five Forces that shape industry competition (Porter, 2008b)

In the rest of this section we first introduce the forces in brief, and then discuss how it is adopted in this thesis. P5F looks at five specific factors that help determine whether or not a business can be profitable based on other businesses in the market. The forces are: 1. Threat of New Entrants The power that a company has in the market can be affected by new entrants of the market and their force. If we consider these new entrants as competitors, in case they possess sufficient capital and can obtain (or already have) sufficient knowledge (know how) to deliver same services, the company’s position may be significantly weakened by the new entrant. 2. Bargaining power of Suppliers If suppliers of firm are not replaceable, they have the power to lift up the price of services and goods that they supply to the focal firm. This is directly affected by the risk and uncertainties associated with changing the supplier. If the supplier does not play a unique role then the after-effects are small or even negligible. Therefore the more the focal firm depends on the supplier


45

and the smaller the supplier base is, the more power they have. If we consider suppliers as direct cooperators of any firm, this shows that how important is the relationship among these cooperators. 3. Bargaining power of Customers This force highlights the importance of the customers and deals with how many customers or buyers a company has. This is important when we consider the significance of the customer and what would be at stake if the customer switches to another supplier. Again considering customers as the second important group of direct cooperators (in B2B relationships), the relationship with these cooperators is vital to any firm. 4. Threat of Substitute Products or Service For each and every product or service that a firm produces and delivers to its customers, there can be competitor substitutions. This force then discusses the threat of those competitor substitutions that can be used in place of a company’s products or services6 . 5. Rivalry among Existing Competitors The importance of this force relies in the number of firms that can compete with the focal firm and eventually threaten the company. Typically the competition among existing rivals in the business is the first instance of competition that comes to mind while considering competition. This is in comparison with competition with new entrants and new comers to a business network. It should not be forgotten that suppliers and customers usually seek for competitors of the focal firm in case they are not satisfied. 4.2.2.1

How P5F Model Will Be Used

Now that we have a better understanding on what P5F model is and how it analyzes a firm’s strategic position, we will describe how we will use P5F in this thesis. Since in this thesis we focus on three specific actors–MNOs, TEVs, and SPs–, the P5F model helps us to perform a qualitative evaluation of the focal firm’s strategic position, based on other firms in the market. This positioning is important because it explains where the focal firm fits in the value network and describes the reason for its location in the network. We use P5F as a checklist for each group of firms, separately, in order to identify significant business relationships that are competition and cooperation; in our context. First, we consider suppliers and customers as “vertical cooperators” of the focal firm, and the existing rivals and new entrants as competitors. Next we look for these four instances (i.e., suppliers, customers, existing rivals, and new entrants) and translate them to cooperators and competitors of the focal firm. 6 We

will disregard this “force” in our discussions in section 7.1.

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Although our focus is on competition and cooperation, we believe that this cannot be done without considering competitive behaviors as a major strategic decision for any firm. Hence we benefit from P5F that is a framework that considers competition as key strategy for success while looking for vertical competitors, as well as vertical cooperators. In our analysis in chapter 7, we initially take into account all five forces but utilize the aforementioned four forces for further analysis. In order to be able to do so (in chapter 7), first we put the P5F in the telecom industry context and evaluate the market as a hole. Then we identify the relationships for each group in terms of (a) existing rivals, (b) suppliers, (c) customers, and (d) new entrants. The supplier and customer forces gives us the cooperation relationships, the existing rivalry gives us competition relationships, and threat of new entrants gives us possible competition in the near future. Let us remind that in our cases (this thesis), the discussions are not purely about cooperation (which ARA assumes) or purely on competition (which P5F assumes).

4.2.3

Coopetition Theory

Coopetition’s definition as a neologism coined to represent the ambivalence of competition and cooperation in business relationships (Stein, 2010) and has grabbed increasing scholarly attention. Besides being a business strategy, coopetition has also been used as a framework to understand interfirm relationships in complex setups. Considering Coopetition as an ambidextrous relationship, scholars find this framework paradoxical (Smith and Lewis, 2011). In better words, coopetition is a framework to explain complex market structures where cooperation and competition merge together to form a new perspective (Raza-Ullah et al., 2014; Stein, 2010) for business networks. The business network and the value network then are created based on the relationships between firms. In other words, it is the collection (complex) of relationships that form the network. With regards to interfirm relationships, Kock et al. (2005) believe that traditionally the relationships between cooperators have been in focus when studying business networks and relationships among competitors have received less attention; therefore the focus should be on the latter. As a result, they introduce coopetition as collaborating with direct competitors (Bengtsson and Kock, 1999). This is pretty much aligned with the general theme of research where scholars mainly refer to coopetition as a strategy that embodies simultaneous cooperation between firms (Bengtsson and Kock, 2000; Gnyawali et al., 2008). On the other hand, we believe this may not be the case since exhaustive research on coopetition has been done in the last fifteen years, where the focus is almost always on cooperation among competitors. At the same time, the research on the cooperating firms (e.g. buyerseller firms) generally stops on the cooperation level (Ancarani and Costabile, 2010; Battista and Giovanna, 2002; Ford, 1980; Gnyawali and He, 2006; Gnyawali and Park, 2011; Oxley and Sampson, 2004; Pellegrin-Boucher et al., 2013) and does not expand to possible competition among cooperators.


Figure 4.5:

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Relationships between competitors (based on Bengtsson and Kock (1999))

Hence we would like to focus on the less studied side of coopetition, which is “competition with cooperators” and expand it to wireless ICT. This angle of coopetition is known as vertical coopetition (Lacoste, 2012). We will use the ideology of “cooperating with competitors” (Figure 4.5) for better understanding the relationships between two firms in a value network, but will modify the model to be able to discuss competition among cooperative firms (Figure 4.6). It is very important to note that the main difference between these two interpretations of coopetition is in the end value being delivered to the customer.

Figure 4.6:

Relationship among cooperative firms

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We propose four instances for coopetition, that the original coopetition model just describes the first instance: 1. The focal actor competes over X with competitor B, and then creates cooperation relationship over X. 2. The focal actor cooperates over X with cooperator B, and then creates competition relationship over Y. 3. The focal actor cooperates over X with cooperator B, and then creates competition relationship over X. 4. The focal actor competes over X with competitor B, and then creates cooperation relationship over Y. But what does it mean when firms are competitors or cooperators? One can argue that if the business network is complex and “roles are not as clear-cut as they used to be” (Kock et al., 2005), it is difficult to define competitor and cooperative firms. Focusing on cooperation, we consider Interfirm interdependencies as the main cause of cooperation. A simple instance of cooperation is the supplier–consumer (buyer– seller) relationship. The interfirm interdependencies become more highlighted when we argue that value should be co–created. Focusing on competition, we follow Merriam–Webster’s definition of competition in business that is “the effort of two or more parties acting independently to secure the business of a third party by offering the most favorable terms”. This means that the competing firms would compete over delivering a value to the third entity that in our context is the consumer. As the original model suggests, there are four main relationships among two firms in a value network. We will briefly explain these relationships in this section based on Bengtsson and Kock (1999). The relationships are (a) Coexistence, (b) Cooperation, (c) Competition, and (d) Coopetition. Among these four, “Coexistence” is only a relationship that is just applicable to the case that firms are initially competitors, since cooperators do not just coexist. Coexistence This relationship happens among competing firms. No economic exchange is done and the firms know about each other but do not interact with each other. There is typically a distance between the firms that has a psychological cause. And the competitors’ goals are stipulated independently. Cooperation Frequent exchanges happen among cooperative firms in different domains. In case of cooperation between competitors, cooperation does not mean a stop to competition and a full trust. Furthermore, the firms who have (or form) cooperation relationships with each other typically pursuit common goals. The proximity between these firms is then based on functional and psychological factors.


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Competition Following the definition of competition, competitors set their goals independently but to satisfy a third party most favorably. This means that the goals, in structure, are similar and directly relate to resources possessed by competitors. In case of competition among cooperators, competition does not mean a stop to cooperation. Coopetition This relationship can include both economic and non-economic exchanges. When competing, the dependence is related to the actor’s strength and position in the business network, and is more equally distributed. On the cooperation side Goals are jointly stipulated when the competitors cooperate or the cooperative firms compete. The goals in competition are often object-oriented.

Chapter 5

On Co-Creation of Value to Support Value Networks In this chapter we discuss why it is important to study telecommunication from an economic point of view by focusing on the relationship between technology and economics related to the context of this thesis. This connection is sometimes omitted by the technical community, but it is a key element towards the success of technologies such as 5G and IoT (Alonso-Zarate and Dohler, 2015). We use concepts from industrial economy to discuss the formation of telecom value networks in the presence of other industries, and how linear value chains are unable to serve this ecosystem any more. For this matter we benefit from a known interdisciplinary school of research called techno-economics. In this section we will describe the logic behind value networks and discuss why it is important to co-create value. We will use these discussions to show how traditional telecom actors play different roles in new markets compared to their activities in Mobile telephony. Eventually we discuss the role of future telecom’s value network in Smart Cities1 .

5.1

Techno-Economic Research in Telecommunication

Tele-Economics is a line of research on telecommunications that applies economic research approaches on the knowledge from the technology research. The purpose is to understand the effect that technology development has on different markets and also the market forces affecting the evolution of telecommunication industry. Tele-Economics includes topics such as studying the behavior of telecom market, the organizations within this market, the customers and users. It also includes the analysis of costs and benefits, and the interactions and relationships among different actors, and analysis of operations. 1 The main body of section 5.1 is taken from appended Paper B, and the main body of section 5.3 is taken from appended Paper C.

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CHAPTER 5. ON CO-CREATION OF VALUE TO SUPPORT VALUE NETWORKS

Figure 5.1:

Interactions between wireless ICT and economics (Laya et al., 2015)

On Figure 5.1 we present a descriptive interaction between the two general disciplines, Telecommunications and Economics, highlighting four main stages. The two stages on the left represent demand from the market, which are considered market Pull. This market then corresponds to any market where Telecommunications can play a role or even Telecommunications market thereof. On the right side, the two stages represent the supply for market, which are the technology push (consider all ICTs). The stages Tele-Economics focus on: Needs in technology: corresponds to research showing clear demand in the market for new technology Findings relate to identification of gaps in the market for technology solutions. Technology development and maturation: corresponds to the more technical stage in the interaction. In this stage a technology is either developed or enhanced. The aim of this stage is twofold: • If this stage is the departure research point, a new technology is developed and is then passed to viability study. • If this stage has been reached after finding a need in the market. The gap drives the telecom industry to come up with a technique to address the demand. Viability of technology: corresponds to analysis and performance evaluation of certain technology. This stage is related to work on deployment studies, and cost calculations applied to telecommunications. The relationship between different types of providers of networks and services including construction, operation and maintenance of infrastructure, the infrastructure requirements of services and users, marketing organization for the provision of networks and services and the interaction between technical solutions and on the other hand, market mechanisms, regulation and competition law.

5.2. VALUE, VALUE CHAINS AND VALUE NETWORKS

53

Innovation in the approach of using the technology: corresponds to research and innovation in the market and economic space to find novel methods to benefit from a technology. This stage is not related to technical development and is more focused on regulation and market structures including demand analysis, analysis of value and behavior models for pricing. Additionally, it involves topics regarding the relationship between the service/network provider and users, analysis of the business models and cost structure analysis and the impact of regulation and licensing. Lastly, strategic decision-making by means of game theory methods falls within this stage. The illustrated approach in Figure 5.1 can start from any of the four corners based on the fact that the research is demanded by the market or pushed by the technology. The important consideration is that the stages on either side (left/right) have closer interaction to each other and benefits from repeated cycles, providing input for further researcher before passing to the other side.

5.2

Value, Value Chains and Value Networks

Value is another terminology with many interpretations with often appearance in research and discussion environments. Dobb (1973) described value, in economics, as worth of a commodity in terms of other commodities, or in terms of money. Michael Porter (2008a) defined value as what buyers are willing to pay for products or services. In the context of our research, we define value as a measure of the benefit provided by a good or service to an actor, where according to Keen (2001) it is generally measured relative to units of currency.

Figure 5.2:

Value chains and value networks (Laya et al., 2015)

Michael Porter first introduced Value Chain in 1985 (Porter, 1985) as the interrelated operating activities, which businesses perform, during the process of converting raw materials into finished products. The terminology since then has evolved and been put into different contexts. In 2001 Kaplinsky and Morris (2001)

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CHAPTER 5. ON CO-CREATION OF VALUE TO SUPPORT VALUE NETWORKS

defined value chain as a tool to describe economic activities that are required to bring a product or service from conception to final consumers. Normann and Ramirez (1993a) present a change in the perception of the value chain, by suggesting that it is no longer possible to define fixed positions for firms based on a set of activities along a value chain. Instead, they refer to the value constellations (or value networks) as a model to focus on the overall system, with focus on the value creation. The general difference in the concepts of value chains and value networks is presented in Figure 5.2.

5.3

Telecommunication Value Network in Smart City

When it comes to telecommunication industry, value is traditionally created in a linear fashion. This corresponds to value chains for mobile telephony provisioning illustrated in Figure 5.3. Typically, the way a linear chain is created is that an end to end process is built for creating and transferring the value. Over the time, the process is subject to become more efficient so that it becomes repeatable at lower cost. This means that the unit of a linear business is the process.

Figure 5.3:

Simple value chain of Mobile Telephony and traditional actors’ positioins

As it is illustrated in Figure 5.3, a traditional value chain in Mobile Telephony provisioning corresponds to two major activity blocks. One on provisioning connectivity and the other one on offering connectivity (as the service) to end user while handling the customer relation management. This has made it clear for TEVs and MNOs where to participate in this value chain; TEVs performing “provisioning connectivity” and MNOs provisioning “End User management” and “Service Provisioning”. The positioning strategy for these actors then have been somehow clear and the value chain made it easy for them to collaborate with each other, while competing in each block with similar entities (i.e. other MNOs and TEVs). Now if we introduce a simplified value chain for mart city as illustrated in Figure 5.4, the question on who will take care of which role is not as straightforward as the mobile telephony value chain. This is mainly due to the fact that there are other actors who might be even more competent in provisioning any of the similar blocks. For instance, a specialized M2M cellular network operator can be considered a better option to provide “Connectivity”. Many service providers have also introduced services for the far right block (i.e. end user management); a previously dominant position for MNOs. At the same time, TEVs and MNOs have

5.3. TELECOMMUNICATION VALUE NETWORK IN SMART CITY

55

shown interest in all illustrated blocks. This is based on the assumption that they can acquire the competences needed to do so.

Figure 5.4:

Simple Smart City value chain and sampled position of actors in the value chain (Based on Ghanbari et al. (2015b))

If we consider that specialized actors in each block can perform comparatively better than TEVs and MNOs, in order to stay in the game as an actor who cannot be overlooked, the traditional actors need to reposition themselves in this value chain. One example of a possible positioning strategy is illustrated in Figure 5.4. The illustrated example then suggests that TEVs and MNOs need to collaborate differently compared to previous example in mobile telephony, since their position is different. For instance, the MNO utilizes the relationship with end-users (i.e. its subscribers), while a service provider offers an OTT service to them (e.g. remote patient monitoring). The telecom vendor offers a M2M platform for this service and the M2M network operator provisions connectivity. Eventually, the same Service Provider offers and manages the M2M enabled devices (patient monitoring devices). The described example shows the importance of dynamicity in taking plausible roles by traditional actors, in case they enter a new market where the setup is different from their comfort zone. But based on the discussions in section 5.2, first we hypothesize that the entrance of new actors and the complexity of roles (activities) forces a change in the introduce value chain; and causes the formation of value networks. This means that the value is supposed to be co-created in a network rather than a chain. By creating a networked business, then the unit of the business is the interaction between different actors while co-creating the value all together and eventually delivering the final product/service to the end user. This directly applies to the case where wireless ICT is helping other industries and is acting as a tool for transforming them. In the next chapters we look into different cases and try to validate the hypothesis on the formation of value networks for future telecom industry. We study the effect of the presence of new actors from other industries and investigate whether it imposes changes on the relationships and the way value is being created traditionally.

Chapter 6

Case Studies and ARA Analysis Providing end users with cellular connectivity has been the primary service in the telecom industry for many years. Long before MNOs, TEVs and SPs started offering other services all the chains of mobile service provisioning were designed consecutively in order to provide end users with connectivity (refer to Figure 1.1). This trend then started to change by the genesis of OTT services on top of infrastructures. As illustrated in Figure 6.1, the infrastructures where long have been the core asset of the mobile service provisioning, now became an enabler for OTT services and the OTT services became the place where the value is controlled and offered1 .

Figure 6.1:

The disruption of value generation and the importance of OTT services

In this chapter we first introduce the role of M2M in the smart city context and describe its important components. Then we introduce studied cases in this context, which will be used as a reference for the rest of the thesis. We follow our discussion of M2M in smart city by proposing an abstract value network for M2M service offerings in the context of smart cities. The abstraction is on the level of actors; meaning that any actor who possess the resources mentioned in this section can perform each role/activity. Next we describe the case of network sharing as an 1 Parts

of this Chapter are taken from appended Papers D, C, and A.

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CHAPTER 6. CASE STUDIES AND ARA ANALYSIS

example of complicated relationships among telecom actors; and use the knowledge gained from this case to better analyze B2B relationships in the former case (in chapter 6).

6.1

M2M in Smart Cities

ICT as a major enabler of Smart Cities is mainly represented by IoT and M2M. On one hand, Telecommunication infrastructures play a vital role in enhancing the connectivity and sustainability of the cities and on the other hand IoT play an important role within ICT for enabling Smart Cities. M2M communications for Smart Cities refers to the exchange of information between autonomous devices in control and monitoring applications without human intervention (Wu et al., 2011). When it comes to Cellular M2M different actors are trying to position themselves in the M2M market by providing different set of solutions, including information management, network deployment, systems integration and so on (Laya et al., 2015). Telecom actors are no exception in this regard. TEVs and MNOs are the prime leading telecom actors that have one way or another taken part in development, as well as benefits of this concept. Moreover, the pressing situation faced by telecommunication operators, triggered by the saturation of their traditional revenue streams (voice and data) in developed countries (Wu et al., 2011) is also resulting in an increasing interest in the interconnection of smart devices and sensors by operators. At the same time there are new actors that are also seeking for strong positions in the M2M ecosystems, targeting different roles. All of these lead to co-existence of many actors who are competing in the same market while they need to cooperate in order to benefit fully from opportunities.

6.2 6.2.1

Case Studies Intelligent Transportation Systems

Intelligent Transportation Systems (ITS) as a building block of Smart City is the application of advanced information and communications technology to surface transportation in order to achieve enhanced safety and mobility while reducing the environmental impact of transportation. Connected Vehicle Services (CVS) is then a specific service within ITS that is commonly defined as the set of services based on ICT and provided during the driving experience. In this section we introduce two cases in CVS. Volvo Connected Car Volvo is currently offering a service named Volvo Sensus Connect™, which basically is a commercial offering embedded in Volvo vehicles that allows the user to obtain services related to and enabled by ICT. This concrete commercial offering has been commercialized in the US. The setup for the Volvo Sensus Connect™ has been aiming to enhance collaboration between numbers of actors, allowing each

6.2. CASE STUDIES

59

actor to focus on its field of expertise. The activities are distributed as follows: AT&T is taking care of connectivity and SIM card provisioning, Ericsson is in charge of monitoring, management and automating connected devices deployment, and Volvo is providing end-user management. On top of the Volvo Sensus platform, OTT providers can offer their own services. An example of these services is media streaming services like Spotify or Netflix. The value network is shown in Figure 6.2.

Figure 6.2:

Tesla vs. Volvo (Ghanbari et al., 2016)

Tesla Motors Being one of the most innovative car manufacturers in the world and aiming to disrupt how the car industry works, Tesla Motors has a slightly different approach regarding Connected Vehicle services. Tesla Connected services are taking this concept one step further, fostering ideas like software updates enabling autonomous driving in passenger car. The concrete case we are considering is the service offering for the Nordic region. In addition to be a cutting-edge car manufacturer, Tesla has selected a different approach when developing Connected Vehicle services. Tesla’s strategy has been integrating and controlling all possible activities vertically. Therefore Tesla concentrates activities on end-user management and in monitoring, managing and automating connected devices deployment; leaving connectivity provision and SIM card provision in hands of Telia. In a similar way as the previous use case, OTT providers are enabled to provide their services on top of Tesla platform. The setup for the Tesla motors use case is shown in Figure 6.2. 6.2.1.1

Digital Built Environment

Broadly defined, the term Built Environment refers to the human-made space in which people live, work, and recreate on a day to day basis (Ghanbari et al., 2016). It provides the setting for human activity, ranging in scale from buildings and parks or green space to neighborhoods and cities that can often include their supporting infrastructure, such as water supply or energy networks. Smart Grids and Waste

60


Management then are two services within this building block that we will present two case studies from them. Consorcio Energético Punta Cana Macao The Dominican Republic has been facing a number of energy challenges in recent years that are mainly related to sub-standard services, inadequate capacity and frequent black outs. These challenges are also connected to its increasing importance as a tourism destination. In order to tackle these challenges the sector has gone through a process of liberalization, where companies like CEPM have provided innovative energy solutions. One of the services provided by CEPM is: reliable Advanced Metering Infrastructure (AMI) solution which would withstand rigorous power fluctuations and provide remote monitoring and management of its electrical grid. Together with (General Electric) Digital Energy™and Ingenu, CEPM has enabled over 24,000 smart meters to speed power restoration and increase reliability of services to CEPM’s customers. The solution offered robust, two-way communication between CEPM and its end users, providing accurate reporting and monitoring of energy operation and consumption. Due to its limited infrastructure investment, CEPM was able to deliver energy services cost-effectively, resulting in significant savings to its customers. In this setup Ingenu plays the role of connectivity provider and GE Digital Energy provides different devices needed i.e. smart meters. The underlying communication technology used to enable these services is Random Phase Multiple Access (RPMA), a low-power wide-area channel access method used exclusively for M2M communications (Figure 6.3).

Figure 6.3:

Bigbelly vs. CEPM (Ghanbari et al., 2016)

Bigbelly Solar Inc. Bigbelly Solar Inc. provides solutions for the management of waste and recycling (Bigbelly Solar Inc., 2015). It offers solar intelligent waste collection systems to manage the process of collecting solid waste, as well as solar compactors, and companion recycling bins and kiosks. CLEAN™by BigBelly is a wireless network

6.3. ARA ANALYSIS OF WIRELESS ICT IN SMART CITY

61

for monitoring and management software that provides real–time and historical data to managers/workers to plan waste collection routes and pickups; Connect™is a turnkey smart waste and recycling system that ensures customer engagement and satisfaction. It serves municipalities, cities and towns, college and university campuses, parklands and beaches, government and military installations, and institutional customers (Bigbelly Solar Inc., 2015). An elaboration on how Bigbelly works as a system in the US is as follows: • Compactors are upgraded with wireless hardware. • CLEAN sends data through standard SMS format to its online server (requires adequate cellular phone signal, currently provided by AT&T). • Operational data becomes real–time. • Collecting is monitored to eliminate unnecessary pickups and free up workers from on-street status checks. In order to provide these services the activities are distributed as follows: AT&T providing connectivity and SIM card provisioning, Ericsson in charge of monitoring, management and automation of connected devices deployed and Bigbelly handling device provision and software service provision (visualization and management tools for cities). This setup is shown in Figure 6.3.

6.3 6.3.1

ARA Analysis of Wireless ICT in Smart City Activities

Looking into provisioning M2M-enabled services based on studied cases, as well as collected data; we identify a set of major activities. Although these activities may differ from different actors’ perspectives, an impartial look on the exiting services and vertical solutions highlights these activities as the most important ones that need to be taken care of in a smart city M2M ecosystem: 1. Provision MTC network 2. Provision M2M device 3. Provide Connected Device Platform (CDP) 4. Provide Application Enablement Platform (AEP) 5. Provision M2M service 6. Manage Customer relation

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Figure 6.4:

Framework to study activities in M2M ecosystem (Ghanbari et al., 2016)

We divide these activities into three main domains based on ETSI M2M simplified architecture for Smart City ETSI (2015), which illustrates how a simplified M2M architecture applies to Smart City; on top of physical layer. These domains are Service2 , Connectivity, and Device (Figure 6.4). In each domain there are some activities that are performed by providers and one activity that is performed by the end user. All the end user activities then comprise one horizontal layer that corresponds to the Customer Relation Management (CRM) activity. The CRM activity is typically performed by the actor who is in direct connection to the end user. All these complexities then suggest that there is a need for a model to study the activities in the smart city-M2M ecosystem. Hence, in Figure 6.4 we introduce a framework to study M2M activities in the smart city context; although we believe it is applicable to most M2M-enabled services. The framework illustrates the relations among activities in terms of interdependencies, as well as the sequence of activities to be performed. The main idea behind implementing this formation is to present the value flow El Sawy and Pereira (2013). This framework will eventually facilitate the process of distributing responsibilities among actors and also helps 2 The

term “Service” here refers to services enabled by M2M, i.e. M2M-enabled service


63

identifying the actors and possible grouping of activities to be performed by one actor. M2M Platforms An important part of the M2M ecosystem comprises the platforms, which includes CDP and AEP (Namiot and Sneps-Sneppe, 2014). Correspondingly, provisioning these two platforms is considered as major roles in the value network. 1. Connected Device Platform: CDPs are software elements that facilitate deployment and management of connected devices for M2M applications over cellular networks. CDP allows devices to connect to Cloud and should be compatible with different software platforms (e.g. Java, Android, etc.) in order to include as many devices as possible. CDP is usually a service portal that covers billing and policy control, bearer service, service ordering and subscription, and SIM card management. 2. Application Enablement Platform: AEPs are designed to provide the core features for multiple M2M applications. They ease the data extraction and normalization activities, so M2M applications and enterprise systems can easily consume machine data. AEP also includes developing tools, enabling developers to create new M2M applications and services. Manage Customer Relation Prior to the physical connection between machines and the cellular network that is supposed to be taken care of by the access network, there is the major need of managing the relationship with customer, i.e. the so-called CRM with regards to end user. This activity is then the process of initiating the relation between the end user (whom are the ones using the M2M-enabled services) and “taking care” of end users. Therefore it can be accepted that this activity is typically coupled with the end service that is being offered to end user by either the OTT service provider or the device provider, whom is the SP in this case.

6.3.2

Resources

When it comes to the role of telecommunications in Smart City, a set of resources enable the telecom actors to participate and perform different sets of activities. The importance of these resources lies in the fact that possession of any of these resources enables an actor to perform a specific activity. The term “resource” refers to anything which could be thought of as a strength or weakness of a given firm. More formally, a firm’s resources, at a given time, could be defined as those, tangible and intangible, assets which are tied semi-permanently to the firm (Caves, 1980). Examples of resources are: brand names, in-house knowledge of technology, employment of skilled personnel, trade contacts, machinery, efficient procedures, capital, etc. (Wernerfelt, 1984). Defined pedagogically, Grant (1991) categorizes

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Resources into six major categories; Financial, physical, human, technological, organizational and reputation. Resource-based theory of studying markets (Barney and Clark, 2007), and focusing on the position of a firm in a chosen market (Porter, 2008a) are two main streams of discussing a firm’s positioning in a value network. Therefore, according to identified activities, it can be concluded that the major resources that enable the activities are as follows: 1. MTC infrastructure 2. Application Enablement platform 3. Competence and know-how 4. Data 5. End User 6.3.2.1

MTC Infrastructure

When providing communication services, the need of communication networks appear naturally. Within communication networks two different types can be identified: Core Network and Cellular Access Network. The core network is the central part of the communications network, facilitating the connection between different sub-networks. The cellular access network (also known as radio access network) is the interface between the end-user and the core network, basically using wireless technology. The MTC Infrastructure is traditionally owned by a MNO, since it is the same as the mobile telephony cellular infrastructure. In the introduced cases, we also have seen emerging actors who are specialized MTC Network Operators who own their own infrastructure. 6.3.2.2

Application Enablement Platform

A software platform that acts as a common ground for development of services and applications on top of the physical infrastructure. AEP can also provide an open environment for collaboration between industries and support innovation in the context of smart sustainable cities. 6.3.2.3

Competence and Know-How

Capturing value from knowledge assets and know-how is not a new phenomenon in economic, and business theories (Teece, 1998). Teece (1981) believes that “economic prosperity rests upon knowledge and it useful application.” And the exploitation of such know-hows in technology is a major source of creation for wealth. Kuznets and Murphy (1966) also believe that “the increase in the stock of useful knowledge and the extension of its application are the essence of modern economic growth.” So we can argue that competence and know-how are intangibles that can even be


65

the source of competitive advantage. We believe that the emergence of know-how as an asset (resource) is not merely due to its essentiality of it for manufacturing products or creating services, but according to Teece (1998) because of the rapid expansion of goods and factor markets, intangible assets become the main basis of competitive differentiation in many sectors. As a result the role of Intellectual Property Rights (IPR) in this scope is quite important. IPRs in essence keep the rights of any know-how for the holder of the rights, where they typically comprise patents. 6.3.2.4

M2M Data

One very important resource when introducing Smart City and M2M services is the data originated for the End Users on the city. Data can be defined as all the information obtained from the usage of a number of services in the city environment; communication/Internet services, transportation services, energy consumption, carsharing, parking or logistics. The added value in Smart City comes from obtaining a big amount of data, process the data and extract useful information for decision making in the city. The data is generated from a number of different sources and stakeholders, going from the MNOs and service providers to the city governance. This data needs to be shared in order to apply analytics and the information obtained needs to be open and usable, first to the decision makers and later on to the other partners involved in the provision of services. Therefore data is considered as one important resource to be shared in this context, being of key importance in the provision of smart cities services. 6.3.2.5

End-User

The final goal of M2M/MTC-enabled services is to provide useful information and OTT services to the End User, which will be able to make better decisions on how to interact with the city. In the provisioning of services, a number of actors are involved and it is not feasible that the End User has relation with all of them. The usual relations with the user are with either the service provider or the M2M device provider (in some cases), since they are both in the front-end of the business activity. In this sense, the different stakeholders are sharing this resource event though not all of them have direct relation with it. It could be concluded that customers are the economic resource which are subject to be cultivated by the producer (Ghanbari et al., 2015b). Short Discussion on Importance of End User as a Resource: One of the key differences between B2C and B2B interactions is the attitude towards customers. This is somewhat of an over simplification but B2C industries tend to act as if customers are an infinite resource that is constantly replenishing itself. Therefore it does not matter if you err on the side of over-extracting value

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from them. Churn is fine because there are always “plenty more fish in the sea”. Remembering the comment by Vargo and Lusch (2004) on end user co-creating value together with the rest of the network, Basole and Rouse (2008) argue that End Users besides value co-creation determine the activities in the value network. B2B industries are generally more aware that their customer universe is a resource to be husbanded. It is finite and, while there is some natural attrition and expansion, it is best to assume that a lost customer will remain lost, and will not be easily replaced. Furthermore, B2B customers talk to one another, so bad treatment of one customer by a supplier tends to have wider repercussions (a dynamic that B2C industries are only now getting to experience as a result of social media). Short discussion on importance of costumers On economic terms, what is important for a firm is higher profit. Profit is a financial benefit that is realized when, in a business activity, gained revenue is more than all expenses (including taxes and costs). The source of the revenue gained by the firm is then the price the customer pays. Revenue for Producer = Price paid by Customer ú Number of customers

(6.1)

At the same time, by considering that Value for the producer is reflected as financial profit; value is the difference between the revenues that the firm receives and the costs of producing the product/service: Value for Producer = Revenue ≠ Expenses

(6.2)

On the other hand, for the customer, value is defined as the ratio between the benefits they receive and the price they pay. Value for Customer =

Benef it P rice

(6.3)

So it means that more profit for the producer can be gained by: 1. Creating more benefit for customers, which means that at the same value (for customer), the producer can charge the customer for more price. This results in more “price paid by customer” and eventually more “revenue for producer”. 2. Increasing the number of customers, and 3. Lowering expenses, which create more value for producer. As a result We can see that the customer plays an important role, when it comes to financial terms, for survival of the supplier (producer); no matter this costumer is an individual or a business entity. In other words, sometimes customers are considered as economic resources to be cultivated by the supplier. On the other hand, the deficit of resources possessed by one actor, typically, leads to “resource


67

dependency” (Basole, 2009) when the producer wants to create a service/product. This way the producer (supplier) needs to interact with its customers and benefit from their resources3 in the creation of the product/service. As a result it is a major concern when a supplier would like to jeopardize profit by causing discomfort in relationship with its customers by possibly competing with them. This is important when competition comes after cooperation; when an existing cooperative business relationship (e.g. supplier-customer) is ongoing and then competition occurs. We will elaborate this matter in sections 7.2 and 7.3.

6.3.3

Actors

We argue that there are other actors rather than traditional telecom actors who might be even more competent in provisioning any blocks of M2M activity framework. An instance is a specialized M2M cellular network operator (MTC network Operator) can be considered a better option to provision MTC networks. Other instances of newcomers performing traditional roles are Service Providers of M2M solutions taking control of the entire value network by handling the end user (EU). This is a previously dominant position for MNOs (in Mobile Telephony). At the same time, TEVs and MNOs have also shown interest in different activity blocks of the M2M activity framework. This fact proposes a theory that it is more relevant to present abstract actors in form of a value network–in terms of business relationships–in order to show the position of firms relative to each other and serving the end M2M-enabled service to end user. This way, any firm, regardless of their traditional business, based on the resources and competences they possess can be put in the value network. The abstract value network then can illustrate the business relationships for any such firm. According to Figure 6.4 each activity can be performed by one actor in the value network, while the end value is being co-created by the network. This idea is also approved by the case studies presented earlier. The only concern is then provisioning AEP, where the case studies show that AEP is typically provisioned together with the service and in some few instances as a complement to the CDP. Therefore the role of AEP provisioning is not a stand-alone role in the value network. As a result we introduce the following abstract actors: • MTC network operator • MTC device provider4 • MSP • Service Provider 3 These

resources can vary from know-how to physical material MTC device providers are the non-ICT industries service providers (i.e., SP). The term MTC device, in our setup, refers to devices that have MTC/M2M modules for connectivity, but perform much more capabilities; e.g., Connected Cars, Smart Waste bins, Smart Meters, etc. 4 The

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A major actor in this setup is the entity that performs the role of provisioning CDP. It can be seen that this activity is mainly performed by the firms who have a background in provisioning connectivity in the sense of automating connected devices. Some examples can be either outsourcees of network operations for MNOs or the ones which have been active in automation of other industries (e.g. General Electric, Siemens, etc.). The so-called MSP actor is the firm that takes this role. It should be mentioned that AEP provisioning, in case of bundling as a complement to CDP, is also performed by this actor. Accordingly, we introduce Figure 6.5 that illustrates two abstract value networks for MTC-based mobile service provisioning. In these networks the abstraction is on the firm level that means any actor who owns the resources-competences associated to each activity can perform the activity. The major difference between these two instances is the interaction with end user. In the model on the right, the SP is the firm that interacts with the end user. This happens when the device is part of the service and the main value is delivered by the service and not the device. An example is the case of smart meters. The electricity meter is typically offered to the end user by the energy company, although the energy company is offering the device as part of the service (that is metering energy consumption).

Figure 6.5:

Two M2M Value Network instances in Smart Cities

The model on the left then presents the case where the device provider initiates the relationship with the end user by offering the device, since the device itself bears a value of its own. The device provider then maintains this relationship via offering M2M-enabled service as an add-on (e.g. M2M services offered on personal vehicles). In this case, the services over the top of this device are also being offered through the device provider to the end-user, which means without this channel there is not a possible way to offer the OTT services to the end user. The device provider holds the role of interacting with the end user, mainly because of the notion of the device (as a platform for services). This case can mainly happen when the device provider is the service provider from the industry (non-ICT) itself, and is offering

6.4. SHARED INDOOR CELLULAR NETWORKS

69

services of its own (the case that we formerly called it SP). For instance when an automotive company is offering a “connected car”, the car as a the M2M device is holding a high value in the service provisioning and also serves as a platform for other services to be offered on top of it. This situation is typically profitable for the device provider in case they have an ongoing relationship with the end user, which is gained via a M2M-enabled service by the device provider/SP itself. The three actors under study–MNO, TEV, and SP–typically take different roles from the aforementioned value network based on their business models. On one hand the resources these actors possess, as well as the competence to perform the activity is a major reason that they play any specific role. On the other hand, other reasons such as where to position the firm in the value network, who to compete with, who to collaborate with, and external forces also affect the strategic decision of which role/s to take. We will elaborate this matter in chapter 7. Therefore, here we present a table illustrating what are these actors capable of, according to their traditional business and resource/competences (Table 6.1). We will use this table in section 7.1 together with our ARA analysis of Wireless ICT in Smart City, in order to find possible vertical Cooperators and vertical competitors for groups of firms under study (i.e., MNOs, TEVS, and SPs). Table 6.1: Who is capable of what activity? Actors Activities

MNO

MTC network provisioning

4

TEV

MTC device offering CDP provision

4 4

AEP provision

6.4

SP

4 4

4

Offer M2M-enabled service

4

End User relation management

4

Shared Indoor Cellular Networks

Network sharing, as an instance of mobile service provisioning, can help us in a better understanding of relationships among actors in telecommunication industry. We, specifically, introduce the case of shared indoor cellular networks and discuss how do value networks emerged due to presence of new actors and how traditional actors are positioned in this system. We also discuss the motivation of cooperation, as well as the role of new (entrant) players in indoor cellular networks ecosystem.

70

Figure 6.6: (2015b))


Joint Venture and Merger value networks in network sharing (Based on Ghanbari et al.

As the supporting technologies for provisioning cellular networks has improved and the demand has gone higher, the cost of provisioning networks for MNOs as the prime owners of cellular radio networks has also raised. With the deployment of different access and core technologies (e.g., UMTS, LTE), which require changes in the network, the cost pressure on the mobile operators greatly increases. Therefore, the high demand for data traffic in the new generation of mobile communications (i.e., 4G/5G) needs a drastic combination of all available wireless technologies. As a common consequence, a new viable business model emerges, in which two or more mobile operators share a common network infrastructure (Figure 6.6). This reduces deployment and operation costs, and decreases the time to market (Beckman and Smith, 2005). Indoor locations, as the place where most of the cellular capacity and calls are originated, have long been subject to coverage issues. In order to improve indoor coverage two types of solutions are widely used; Distributed Antenna Systems (DAS) (Beckman and Smith, 2005) and repeaters. Here competing operators cooperate with each other and also with the facility owner and/or with companies using the indoor infrastructure. In this multi-operator settings the physical infrastructure i.e. the DAS network and the repeater equipment, is shared. However, the radio capacity (the base stations), the spectrum and the access control are managed by each operator. In the business domain a DAS solution is fully transparent since each operator provides the capacity using own radio equipment and spectrum. An operator can independently provide more capacity to its own indoor users by upgrading the base station equipment. The indoor cells are part of the overall operator network, the base stations in the radio access network of each operator are connected to the respective core networks. From a business perspective this is business as usual for the mobile operators, the operators fully control their own cells and there are no potential problems when it comes to sharing of the radio resources. In this case the role of a third party actor can be to own and/or to maintain the indoor DAS

6.4. SHARED INDOOR CELLULAR NETWORKS

71

infrastructure. The ownership of the DAS system does not have any implications when it comes to the end-users or the traffic. The new business interaction then is among the MNOs and the DAS operator, who is the new entrant to the value chain and plays a supplier role for MNOs. The presence of DAS operator as an actor creates a new node in the value chain.

Figure 6.7:

New actors in indoor cellular networks provisioning (Markendahl and Ghanbari, 2013)

For smallcell networks the situation is different. In a typical indoor smallcell network the MNO deploys a smallcell network by the aid of a third party small cell operator in order to improve coverage and capacity. But since the premises owners tend to just have one set of such infrastructures installed in their premises, MNOs have to share infrastructure in order to guarantee their presence. The main actors in this setup consist of MNOs, TEV, Premises Owners, and a third party smallcell operator. There are multi-operator smallcell solutions where both the base stations as well as spectrum and access control are part of the shared solution (Figure 6.7). We consider the two following cases in indoor network sharing: • Multi-operator access to a local radio access network, operated by a local operator, by use of roaming. • Multi-operator access to a common radio access network enabled by gateway or multi-operator core network (MOCN) solutions.

72


Figure 6.8:

Shared indoor cellular network’s value network

The operation and management of the indoor network, based on the used sharing model, is typically done by an outsourcee. For instance, in case of MOCN sharing, since the smallcell gateway is located at the customer’s premises and shared among different operators, it is more admissible to operate the network by one singular outsourcee who controls the existing smallcell network and gateways. The third party smallcell operator is a new entrant to the ecosystem in this case that performs a part of MNOs’ typical business in macrocell network. Acting as a managed Service Partner (MSP) in this value network, the MSP here operates a shared network on behalf of MNOs and/or Joint ventures (Figure 6.8). Therefore, the presence of the new actor who does not fit in any linear chain for creating value cause a new formation for the ecosystem. The new format is a value network that substitutes the value.

Chapter 7

Analysis and Discussion In this chapter we put our three groups of firms under study (i.e. MNOs, TEVs, and SPs) in the abstract value network introduced earlier. We use the value network (Figure 6.5) together with data from case studies, and question what would happen if any of the three groups of actors perform either of the activities in Table 6.1. If we consider each group as the focal firm, we discuss the business relationships between the focal firm and different actors of the value network. We adopt the definition of relationships from Ford and Håkansson (2013a), which considers “intense interactions and economically important interdependencies” between firms as relationships. To perform this analysis we use Porter’s five forces model (P5F) as a checklist for identifying important business relationships for the focal firm, while considering all important forces of the market. As a result of this analysis we determine the positions in which MNOs, TEVs, and SPs would possibly cooperate with each other and/or compete. In places where the cooperation and competition happen simultaneously, we call the relationships coopetition. Hence the main findings based on analysis are presented in section 7.1 and 7.2, and accordingly the findings are discussed in section 7.3, in order to see their implications1 .

7.1

Analysis of Competitive Forces in Telecom Industry based on Presented Case Studies and Observations

7.1.1

Competitive Forces of Market in Telecom Ecosystem

In order to be able to use P5F, first, there is a need for a general discussion on P5F on the telecommunication market as a whole. Hence we put the Porter’s forces into the context of our discussions, which is telecommunication and wireless ICT ecosystem. In this step we discuss each of the forces from the market’s perspective in order to get a better understanding of the view point of any involved actor in this ecosystem. We benefit from this in the next step of our analysis that is detailed 1 Parts

of this Chapter are taken from appended Paper E.

73

74

CHAPTER 7. ANALYSIS AND DISCUSSION

P5F analysis for MNOs, TEVs, and SPs. Accordingly, in the next step we focus on the three groups of firms under study. Threat of New Entrants In the old telecom value chain, as a consequence of intensive dependency to capital, the most significant barrier to entry was access to finance. In the future telecom industry, where telecommunication plays the role of enabler for services, the situation is different. When services co-created by multiple actors, or services created over the top of other products bear the value, the threat of new entrants escalates. These new entrants, according to the definition by Porter (2008a), are firms that enter a market and become competitors to existing firms in that market. For instance, if we consider ownership of a telecom frequency spectrum license as a major entry barrier for new mobile operators, in case there is a possibility to provision mobile networks with unlicensed spectrum, many new actors would enter such markets. These new entrants then would possibly threaten the business of existing traditional actors. We should not forget that in some cases these are the existing actors that become new entrants. This happens in case a traditional actor enters the market of another type of actor; for instance when TEVs start to offer similar services as MNOs offer to customers. A direct example is when TEVs offer IoT connectivity provisioning. At the same time, we introduce yet another category of “new entrants”. These are the firms that did not exist in the telecom market before, and accordingly not in the value chain as well. But with the presence of telecom industry in other industries, they appear as a new entrant to the telecom ecosystem and the newly created value network of telecom. We discuss the presence of both types of new entrants in section 7.3, while remembering that these two instances of “new entrants” should not be mistaken with each other. Power of Suppliers In the context of value networks, unlike value chains, suppliers have a less critical position. At the same time there are actually large number suppliers around willing to become part of the telecom-enabled service. Vendors, arguably, are not the sole supplier of the value chain any more. MNOs, Vendors, Software Based Systems & Solutions providers (SBSS), and even Service Providers in different settings become suppliers to each other since the creation of value does not follow the same linear chain any more. As a result, the bargaining power of suppliers is diluted. Power of Customers With introduction of variety of telecom-enabled services and demand oriented service provisioning, the bargaining power of buyers rises. Traditional telecommunication services such as connectivity have become a commodity and their availability can be taken for granted. This translates into customers seeking low prices from companies that offer reliable service. Switching costs are relatively lower for end user but higher for those in need of customized solutions, but still buyers intend to avoid lock-in and vendor lock-in effects. At the same time, due to the power of

7.1. ANALYSIS OF COMPETITIVE FORCES IN TELECOM INDUSTRY BASED ON PRESENTED CASE STUDIES AND OBSERVATIONS

75

business customers who own a considerable share of end users, suppliers tend to offer tailored solutions for their customers, just not to lose the revenue. Availability of Substitutes Services from non-traditional telecom actors pose serious substitution threats over traditional products/services. Specialized actors who focus on a specific activity and target niche markets also have emerged that their services are comparatively well designed. At the same time, some traditional actors step in and perform same activities as their suppliers/buyers in another setting would offer and they can offer the same service to the end user. Competitive Rivalry Competition is fierce. New entrants, previous suppliers overtaking buyers position, previous customers overtaking suppliers position, substitute services made by similar firms, different constellations working together to create value, and more global offerings are enough reasons to worry about competition. Limiting competition to the existing rivals, similar firms and replacement by previous customers/suppliers seem to be the highest threat in terms of competition.

7.1.2

Other Actors of the Telecom Ecosystem

Now that we have a better understanding of market forces, we introduce other possible traditional actors that perform the presented activities mentioned in section 6.3. We use this list in the next section, together with three groups of actors under study (i.e., MNOs, TEVs, and SPs), to be able to perform a through P5F analysis, in order to have a complete picture of Suppliers, Customers, and Existing rivals. We remind that, as stated before, the industry service providers are the same entities as SPs. OTT service providers are then, typically, the small businesses that just offer services over the top of the existing infrastructure/services. These actors are: 1. OTT SP (e.g. Spotify, Facebook, etc.) 2. CRM & billing solution providers 3. SBSS that are typically non-wireless ICT firms (sometimes referred to as IT companies). These firms mainly offer measurable performance improvements in an operator’s business processes with software that is scalable, configurable and provide end-to-end capabilities. They develop and deliver software-based solutions for OSS and BSS, TV and media solutions, as well as solutions for the emerging m-commerce ecosystem. We consider that Business Customer Support and Consulting and Systems Integration (CSI) companies also belong to this group. 4. Device provider, which refers to companies that manufacture the devices which will be offered to end user in this value network. This is the same device that is enabled by M@M capabilities.

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CHAPTER 7. ANALYSIS AND DISCUSSION 5. Specific MTC network provider a) Wide area wireless communication providers: e.g. Sigfox. b) Indoor communication providers: e.g. Wi-Fi companies such as Aptilo. 6. Special CDP providers (e.g. Jasper, Sierra wireless, Wyless, etc.). 7. Special AEP provider (e.g. ThingWorx)

7.2

Coopetition Points in Future Telecom

In order to find the coopetition points in future telecom ecosystem, now we take the three actor groups (i.e., MNOs, TEVs, and SPs), separately, and put them in the P5F model. We do this analysis based on the case studies presented in section 6.2, Table 6.1, and the discussion in the beginning of this section (on putting PF5 in the telecom context). Among the five forces of P5F model, we eliminate the “Threat of substitute products” force as we have delimited the model to our use. Besides the three groups of actors under study, we also use the aforementioned list of important actors in order to find a comprehensive list of possible existing rivals, suppliers, and customers. It should also be mentioned that while looking for new entrants to apply them in the P5F model, at this stage, we consider those actors that–based on Porter (2008b)–become horizontal competitors to existing actors after they enter the market; and not vertical competitors. The results are presented in Table 7.1, Table 7.2, and Table 7.3. Table 7.1: Activities that traditional MNOs are likely to perform Existing rivals

Suppliers

Customers

New entrants

MTC network provision

1. MNO 2. Capillary NW operator

1. TEV 2. SBSS

1. Device provider 2. Sp

Specific MTC network provider

MTC device

-

-

-

Specific CDP provider

CDP provision

1. MNO 2. TEV

1. TEV 2. SBSS

1. Device provider 2. SP

AEP provision

-

-

-

-

Offer M2M-enabled services

-

-

-

-

CRM

-

-

-

-

7.2. COOPETITION POINTS IN FUTURE TELECOM

77

Table 7.2: Activities that traditional TEVs are likely to perform

MTC network

Existing rivals -

MTC device

-

-

CDP provision

1. MNO 2. TEV

SBSS

AEP provision

1. SBSS 2.SP -

M2M services CRM

-

Suppliers

Customers

-

-

New entrants -

-

-

-

1. Device provider 2. SP 1. SP 2. OTT SP -

-

-

SBSS

Specific CDP provider Specific AEP provider -

Table 7.3: Activities that SPs are likely to perform Existing

Suppliers

Customers

-

-

-

SP

Device provider

CDP provision

-

-

AEP

1. SBSS

rivals MTC network MTC device offering

provision

2.SP

1. End User 2. OTT SP 1. Device

n/a

provider 2. OTT SP

New entrants n/a Specific AEP provider

1. MNO 2. TEV Offer M2M services

3. Device SP

provider 4. SBSS 5. Specific AEP

1. End User 2. Device Provider

n/a

3. OTT SP

6. Specific CDP CRM

Device provider

n/a

1. End User 2. OTT SP

n/a

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Based on presented analysis of the competitive forces in Wireless ICT (section 7.1) and according to Table 7.1, Table 7.2 and Table 7.3, first we argue how competition and cooperation happen in this industry. Then, if they happen at the same time, we translate these two instances into Coopetition. Based on the tables, on one hand, if any of the three actors beside the focal actor exists in the “existing rivals” column, this means competition with the focal actor. On the other hand, if any of the three actors beside the focal actor exists in the Suppliers-Customers columns, this means cooperation with the focal firm. According to the above definition, we derive the instances of coopetition from the tables in form of competing with cooperators. These instances are directly aligned with the second derivative2 of coopetition model, proposed in section 4.2.3: 1. Considering MNO as the focal firm, there is a competition with TEVs over CDP provisioning while at the same time TEVs cooperate as supplying MNOs in MTC network provision. 2. Considering TEV as the focal firm, there is a competition with SPs over AEP provisioning while at the same time TEVs cooperate with SPs as their customer in CDP provisioning. 3. Considering SP as the focal firm, there is a competition with TEVs over AEP provisioning while at the same time TEVs cooperate with SPs by supplying them in offering M2M-enabled service. Now that the instances of competition with cooperators have been identified, instead of looking into cooperation among competitors we can highlight the differences between original coopetition definition and the instances identified in this section. It is very important to distinguish the differences between the two models of coopetition since it gives us a better understanding of the risks and uncertainties associated with competition among cooperators. The original coopetition model argues that the main reason behind cooperation while two (or more) firms are competitors is reaching a higher value, while it cannot be reached without collaborating with competitors. An example of this situation is the network sharing case-study introduced in section 6.4. The logic of cooperation is then synergy, lack of resources, complementing competences, and other forces of market (e.g. regulation and external forces from premises owners in indoor cellular networks). Besides the reasons mentioned before, in cases where competition happens after cooperation is already in place, the need for co-creating value is the main driver for cooperation. The three instances of coopetition mentioned here also approve that although these firms have been already involved in cooperative activities, but still they bear the possibility of damaging the “good” relationships and start competition. The main cause of maintaining the cooperative relationship is then the need of MNOs, TEVs, and SPs to each other for co-creating the value. 2 The focal actor cooperates over X with cooperator B, and then creates competition relationship over Y.

7.3. DISCUSSION OF THE RESULTS

79

The other instances of coopetition, based on the third derivative3 of coopetition are as follows: 4. Considering MNO as the focal firm, there is a competition with TEVs over CDP provision while at the same time TEVs cooperate for MNO’s CDP provisioning as suppliers. 5. Considering TEVs as the focal firm, there is a competition with SPs over AEP provision while at the same time SPs are customers of services by TEVs for SPs’ AEP provisioning.

7.3

Discussion of The Results

Wireless ICT is not the only tool for transforming other industries but indeed is one of the most important tools for most industries. “Digitalization respects no boundaries”4 and this empowers the presence of ICT as the main tool for digitalization in many diverse industries. At the same time, this ubiquitous industry is expected to meet various requirements from other industries due to extensive expectations. Narrowing down the ICT industry to Wireless ICT, these requirements mainly comprise provisioning communications between machines, while enabling them to digitalize and offer more than what they have been offering. The target industries vary from (but do not limit to) Automotive to Health, and e-Government to Digital Built Environment; a diverse set of specific needs and requirements. One major common misapprehension in this process is then to consider all these target industries similar in what they require from wireless communications and try to push for common services and offerings. This is in contradiction to reality where suppliers of any service need to listen to their customers and adapt to the requirements instead of pushing for existing services/products. As we discussed in Chapter 3 (Problem description), the wireless industry actors in this process are facing two major sets of problem; adopting new value creation models, and coopetitive relationships. In the remainder of this section we discuss what do our presented results mean from Sections 6.3.3, 7.1, and 7.2, and what are their implications.

7.3.1

Value Co-creation in Wireless ICT Ecosystem

With regards to the value creation process, the traditional telecom actors have to accept that their main customer segment in new markets such as Smart Cities is changing; and now they are supposed to serve business customers that are industrial service providers. This change is a bigger dilemma for MNOs (compared to TEVs) since their main customer segment has long been End Users; a transition from 3 The focal actor cooperates over X with cooperator B, and then creates competition relationship over X. 4 Erik Kruse, Strategic Marketing Manager and Networked Society Evangelist Ericsson, at Johannesberg Summit 2016.

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“Business to Customer” transactions (B2C) to “Business to Business” transactions (B2B). Since the customer segment for telecommunication industry is changing, the way that traditional wireless ICT actors have been performing their business for long may not be efficient anymore. This argument directly regards to the fact that now with the diversity of customers and needs, the telecom actors as suppliers need to listen to their customers’ requirements (that are quite different from each other) and offer modified, different, and specialized services to each customer. Whether they are capable or not is then yet another concern. 7.3.1.1

Cooperation Among Actors

When it comes to activities that are needed to be performed to provision mobile services for other industries, our results in section 6.3.1 show a complex mix. These activities are then allegedly impossible to be taken care of by just one actor. Since these activates are supposed to create a value in the end, as we argued in chapter 5 and partly in section 2.2.3, we showed that these activities need to be split among different actors. This split is simply just because it is impossible to offer any such solutions for each and every business customer in a vertically integrated manner; since the requirements and demands are so different. It should not be forgotten that the role of the customer is not just to demand the demands, but to take part in the process of value creation. By remembering the essence of the Service-Dominant logic (Vargo and Lusch, 2004), we know that the customer is the major co-creator of value together with the service provider. At the same time, the aforementioned complexity of activities requires “multiple active agents” (Tokoro, 2015) to cooperate over a “certain shared purpose” and co-create the value. As a result we have to consider the future telecom ecosystem comprising a set of actors that all together take part in the process of creating the value; actors that are not limited to traditional wireless ICT actors. 7.3.1.2

Formation of Networks

In section 2.2.3, we have introduced value networks and how they are taking over value chains in mobile service provisioning. Value chain thinking argues that value is created in the dyadic business relationships among firms. At the same time, based on our discussions, we showed that the co-creation concept together with the split of complex activities overrules linear value creation and requires networks and concurrent business relationships among multiple actors. Hence, we highlighted the importance of studying value networks instead of value chains. In this approach it is important to first draw the attention to the actors, and then formulate the types and extent of business relationships among involved actors (Ritter et al., 2004). These relationships can be possibly formed among any traditional actors of wireless ICT, industrial service providers, or even any new firms that consider offering services in this value co-creation process (Basole and Rouse, 2008). For this matter, during this study, we have used the concept of smart city as the main context in order to be able


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to put our discussions into the context. Smart city, as the place where different industries come together in order to make “smartification” possible, is a perfect fit for our discussions regarding the role of wireless ICT in enabling services, cocreation of value together with wireless ICT, value chain to value network transition, ARA analysis5 , competition, cooperation, and coopetition. As the wireless ICT industry is becoming more complex, reasons such as liberalization and lowering the technological barriers to entry (Li and Whalley, 2002) have made a way for co-existence of diverse set of telecom players; both traditional and non-traditional. As a consequence, the industry structure proposed by Fransman (2010), which considers the telecommunication industry a monopolistic three-layered system, is no longer valid and has changed quite significantly towards a more complex and competitive network. Since the number of involved actors in different segments, as well as the level of competition varies in this ecosystem, we argued in section 6.3.3 that it is more applicable to identify abstract actors rather than detailing each existing actor in any market. In contrary, there have been many attempts to categorize these different types of players, which obviously have led to no singular best interpretation. Instances are local, long distance, mobile, equipment providers, Internet access, video and functional services (Fertig et al., 1999); public network operators, backbone network operators, access network operators, service providers and intermediaries (Ballon et al., 2001). Hence, we introduced the abstract value network in section 6.3.3, where the abstraction is on the firm level. This means that any actor who has the competences can pick/take any role from the proposed actors in our value network; and upon that the relationships within the network are possible to be studied and discussed. 7.3.1.3

Customers as the Major Co-creator of Value

Yet another important fact to recall is the presence of the customer in the value network as the co-creator of value. Looking into example case studies presented earlier in section 6.2, we showed how important it is to collaborate together with these customers and how obsolete is the mindset where customers are considered as just the end node of the value chain. At the same time, considering SPs as the customers, it should not be forgotten that the presence of this new entrant in the value network is imposing major changes to the regular business of traditional wireless ICT actors. These changes force traditional actors not only to adopt cocreation, but also to worry about possible threats from the new entrant. According to Porter (2008b) and our analysis in section 7.1–by applying P5F model–, we believe that these firms can “bring new capacity” at the same time having a “desire to gain market share”. This will then directly affect the competition strategies in the market as a consequence of pressure on different elements of the market such as “prices, costs, and the rate of investment”. Let us not forget that we are not talking about small companies here. These new entrants can easily leverage their 5 Erik Bohlin, Professor in Technology Management and Economics at Chalmers University of Technology, 7th ITS PhD seminar, San Lorenzo de El Escorial 2015.

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competences, market presence, capital, networks, etc. to change rules of the game. Instances of such firms in the automotive and transport industry (as an example where ICT is heavily involved) are Scania AB and Volkswagen AG, where Scania still can be considered a relatively smaller new entrant compared to Volkswagen AG that is a larger industrial service provider.

7.3.2

Cooperation and Competition Relationships

So far we have shown and discussed that our hypothesis on the formation of value networks for future telecom industry, as proposed in section 5.3, is valid. We have also shown that the major cause for this change is the emergence of new entrants from other industries in the wireless ICT value creation process. As stated earlier, in this stage the importance of value co-creation, both internal and external6 , is quite vivid for involved actors although the relationships among these actors are not as simple as in value chains. Besides the external process, internal value co-creation also creates complicated business interactions. The internal process is important since traditional actors basically have a supplier-customer relationship in place. In many instances this vertical relationship (e.g. TEV ÷ MNO) simply serves as an aggregated supplier for a third possible actor (e.g. SP) that becomes a customer for the M2M/MTC enablement (i.e. [TEV ÷ MNO] ÷ SP). As we discussed in section 4.2.3 and partly in section 2.2, the most two common types of relationships are cooperation and competition. Let us consider that cooperating firms create a strategic group in contrary to non-cooperating firms. In this case Caves and Porter (1977a) argue that firms in strategic groups tend to avoid rivalry. At the same time, Bengtsson and Kock (1999) and Porter (1979) believe that competition and rivalry increases as the strategic distance between firms increases. On the other hand, this ideology is contradicted by Kwoka Jr and Ravenscraft (1986) where they believe that strategic groups can also experience intensive competition within their group, among the firms of the similar conduct. We believe that, with the emergence of value networks and business networks and the increase of complexity in markets, the idea of competition among cooperators is not far from reality. With the growth of alternatives (both suppliers and customers) (Ford and Håkansson, 2013a) competition in business networks, even within strategic groups, happens more than before. We call this competition among cooperators as “vertical competition” (based on Lacoste (2012)). 7.3.2.1

Vertical vs. Horizontal Relationships

If we simplify and consider the business relationships among firms as Vertical and Horizontal; vertical relations comprise interactions between suppliers and customers (e.g. TEVs ÷ MNOs), and horizontal relations comprise interactions among somehow-identical firms (e.g. MNOs ÷ MNOs). In this thesis we have focused on 6 In our study we refer to internal co-creation refers to cooperation over creating value among traditional wireless ICT actors, while external refers to co-creation together with SPs.


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the relations among firms within the future telecom value network and discussed them in terms of cooperation, competition, and coopetition. Accordingly, we can classify the relationships in six possible categories: vertical cooperation, vertical competition, vertical coopetition, horizontal cooperation, horizontal competition, and horizontal coopetition. Examples of these six instances in traditional mobile telephony ecosystem are given in Table 7.4. Table 7.4: Vertical vs. Horizontal relationships in traditional mobile telephony Relationships Vertical Horizontal

Cooperation TEV ÷ MNO Supplier-buyer MNO ÷ MNO

Competition

Coopetition

n/a

n/a

MNO ÷ MNO

Network sharing

Since in this thesis we have mainly excluded relationships among (somehow) identical firms from our discussions , it means that the main body of our analysis is dedicated to the role of vertical relationships in the process of value creation and the making of value networks. However, in this chapter, we can (and will) benefit from similarities between horizontal and vertical relationships for the sake of our arguments. 7.3.2.2

Vertical Cooperation

When it comes to cooperation, we have discussed benefits of cooperative relationships as well as its drivers briefly in sections 4.2.3 and 2.2. The presented related works showed that the focus in literature is mainly on horizontal cooperation as a major driver for horizontal coopetition. At the same time, the arguments on relational benefits of vertical cooperation are mainly taken for granted. But we highlight the fact that value co-creation is optimized via vertical cooperation that is aligned with Ulaga and Eggert (2006). In this sense many scholars believe that in vertical cooperation, value creation and customer’s competitive advantage are the main drivers (Anderson and Narus, 1991; Cardozo et al., 1992; Day, 2000; Dunn and Thomas, 1994; Dyer and Singh, 1998; Ford, 1980; Grönroos, 1997; Jap, 1999; Lacoste, 2012; Morgan and Hunt, 1994). Hence it seconds our proposed reasoning for introducing co-creation of value as the main source for creating collaborative value networks. 7.3.2.3

Vertical Competition

When it comes to vertical competition, on one hand, competition among cooperators typically comprise indirect rivalry over a product/service that there is no cooperation among the firms for creating it. An example is TEVs supplying MNOs

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by manufacturing radio access networks but competing with them on IoT platforms. On the other hand, in fewer cases, cooperators in wireless ICT compete over the same product or service that they cooperate on creating it for different customers. An example of this instance is then provisioning connected device platforms (CDP). In the case of CDP provisioning, MNOs that offer CDP to a SP (as the customer) typically work hand in hand with a TEV as the technical support, where at the same time TEVs also offer their own CDPs as a service to yet another SP. Now that we see it is possible to compete with cooperators (i.e., to compete vertically), we again highlight the the importance and the need for considering vertical competition, in the making of value networks and presence of new actors in the telecom ecosystem. But, this time competition is not necessarily a show stopper against cooperation and value co-creation. Hence, in our study, we have benefited from two major (and some how contradictory) analysis models; ARA and P5F. On one hand, as a major analysis models that “is built on the assumption that business relationships is the key to success”7 , ARA model mainly covered the cooperation angle of our analyses. On the other hand, P5F model that “is built on the assumption that power leads to higher profits (and better firms)” mainly covered the competitive angle of our analyses. In a general sense, Luo (2007) believes that four major factors drive competition: 1. An increased overlap between firms’ competitive goals, 2. Increased maturity of the industry, 3. Increased symmetry between firms, and 4. Decreased resource dependency between firms. Although this argument by Luo (2007) is basically built for horizontal competition, but we believe that it also holds for vertical competition. An example of vertical competition in the wireless ICT industry is the case where MNOs and TEVs compete for IoT connectivity provisioning8 . The drivers for this vertical competition are no exception to the four factors of competition stated by Luo (2007). The “future telecom” is experiencing more maturity for the enablers of IoT services, which is a result of increased symmetry between firms. It was not long ago that the boundaries among firms was so clear that one could easily distinguish between a telecom equipment vendor and a mobile network operator. Now, firms offer very similar services to their business customers that makes the distinction among firms quite blurry. At the same time, with the emergence of softwarization and the shift from products to services, as well as various overlapping technologies that perform almost similar, the dependency of firms on each others resources 7 Niklas Arvidsson, Associate professor in Industrial Economics and Management at KTH Royal Institute of Technology, peer quality review on current licentiate thesis document, Stockholm, June 2016. 8 We have shown instances of such competition in section 7.2, where we discussed coopetition points in future telecom ecosystem.


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have become less as a result of possible exchange of suppliers and customers. On the other hand, as we discussed in section 6.3.3 and based on identified resources, one can argue that it is now possible that various TEVs either possess or endeavor to achieve resources (including the know–how) that MNOs build their M2M/IoT business upon them. TEVs would do so in order to perform similar activities in the same market; an instance of direct overlapping competitive goals. Expanding this example to the wireless ICT market, in case traditional actors start to build up similar competitive goals with their current vertical cooperators, vertical competition is simply inevitable. Given the example on vertical competition, if the vertical competition happens in the wireless ICT ecosystem, and it does not withhold the cooperation among firms, it results in vertical coopetition. On the contrary, we have discussed an instance of horizontal coopetition in the wireless ICT ecosystem in case of indoor mobile network sharing in section 6.4. This case represents the fact that cooperating with direct competitors is not a new phenomenon in this ecosystem. The forces imposed by a new entrant (i.e. premise owner) on the market drives MNOs that are horizontal competitors to cooperate together in order to ensure their presence inside the buildings. Another instance of horizontal coopetition in the telecommunication industry is Outdoor Network Sharing. In this case, the major drivers for cooperation with competitors are lack of a specific resource (i.e. Spectrum license) and high cost structures for deploying networks.

7.3.3

Vertical Coopetition

Vertical coopetition in definition is similar to horizontal coopetition; a simultaneous cooperation and competition. Coopetition is typically considered a paradoxical (Smith and Lewis, 2011) phenomenon, where the nature of the paradox is derived from the contrast between cooperation and competition. The contrast means that cooperation and competition are in terms of “either/or” (Raza-Ullah et al., 2014), in which firms have to decide to either cooperate or compete where the latter, according to Quinn and Cameron (1988), “represents a situation in which it is not possible to choose between contradictory dualities”. This is in contradiction to Raza-Ullah et al. (2014), where they believe in the “both/and” perspective of the relationship in the coopetition phenomenon. Hence, we call coopetition an ambidextrous phenomenon, in which the paradoxical cooperation and competition are simultaneously happening although it may seem inconsistent (Lewis, 2000). Looking into ambidexterity of vertical coopetition, it is obvious that horizontal and vertical coopetition are indeed different in their essence compared with each other. In Horizontal coopetition the firms are already in a competition relationship and thereafter start to cooperate. This means that the “negative feeling” in the relationship is already in place, but still the firms decide to start cooperation. In the contrary, in vertical coopetition, firms are initially in a cooperation relationship and afterwards start to compete, which means that “negative feeling” comes as a consequence of competition and will probably affect the relationships. Now the

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question is what would happen to the ongoing cooperation among these firms. Would they prefer to stop cooperating with each other, or it does not affect the “positive” relationships? This discussion is accentuated when we recall that the nature of the formation of the value network is the cooperation among firms. 7.3.3.1

Emotional Ambivalence

As a consequence of vertical competition with cooperators, firms can to some degrees get stuck in emotional ambivalence. The concept of emotional ambivalence in organizational relationships (Pratt and Doucet, 2000) can in different cases become a dilemma. Back to our previous example on competition between TEVs and MNOs, if a customer like an MNO sees its supplier as a competitor, considering changing the supplier seems to be an option. This can be an immediate effect of “negative feelings” as a consequence of competitive relationship. Although the investments (both financial and temporal) are high in buying a series of instruments and solutions from a TEV as a supplier, but it is not far from reality to consider changing the supplier to yet another accomplished TEV. At the same time, other TEVs that are horizontal competitors with the supplier in our example would not just “wait and see”. Another side of the story is how the supplier would “feel”. Would the supplier risk having a “good” cooperative relationship by entering in a “bad” relationship? Let us not forget that this situation is not comparable with horizontal coopetition; since in horizontal coopetition the “bad” relationship is already in place. In the horizontal coopetition case “trust” can be an issue; but we will skip that in this discussion. 7.3.3.2

Industrial, Relational, and Firm Specific Drivers

The answer to our recent question is not so straight forward. Interestingly, based on the presented case studies in chapter 6 as well as the conducted interviews, we see that in most cases the firms stay in the vertical coopetitive relationship. Major reasons for such behavior are industrial drivers, relational drivers, and firm specific drivers (Raza-Ullah et al., 2014). Industrial drivers in the wireless ICT industry, first relate to the aforementioned maturity of the market. Although the future telecom with the emergence of SPs is not the same as how it was before, but we believe that the level of maturity is not going to be less. The second related concern for industrial drivers is with regards to high cost structures. In the telecommunication industry the cost structures are relatively high. While Macrocell base stations, as a typical investment example, cost a MNO roughly in the order of 100K euros, the investments in other segments of the business for firms, such as core network, network operation centers, customer relation management, and etc. are quite high and complex. Technology development is another important aspect of industrial drivers. This aspect is without a doubt one of the most promising highlights of the ICT industry and consequently wireless ICT. As we discussed in


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the very beginning of the thesis, technology development is the prime reason for the rapid transformation that the ICT industry is facing in recent years. On the other hand, relational drivers of vertical coopetition are quite straight forward. Without a doubt vertical cooperation or the customer-supplier relationship is a consequence of demanding complementarities among vertical cooperators in the wireless ICT. According to Porter (2008a), relational benefits are generated when involved actors in the relationships achieve a high level of interaction towards a common goal in their business interaction; a phenomenon that is obviously the case in vertical cooperation. The emergence of SPs in the value network, the need for co-creation of value, and the transformation from value chains to value networks is a vouch for relational drivers. Last but not least, firm specific drivers then relate to resources and competence as we discussed in section 6.3.2. As a consequence, lack of either of these resources directly affects the possibility to take over the respective role/activity.

7.3.4

Nonconformity of Vertical and Horizontal Coopetition

Eventually, we can claim that the drivers for vertical and horizontal coopetition are not homologous. One major driver that seems to be common in both cases is direct economic benefits (Lacoste, 2012). But the economic benefits of cooperation in these two cases do not share a common reason. On one hand high cost structure of deploying a specific product (e.g. Radio Access Network) gathers two (or more) existing competitors to cooperate in order to reduce costs. On the other hand high cost structure of implementing a solution/service without the original supplier (e.g. changing the supplier or develop in-house) keeps the competing cooperators to stay in the vertical coopetition. Hence, the economic benefits in vertical coopetition are generally the outcome of the relational benefits (Lacoste, 2012). Another major cause for horizontal cooperation is then lack of a particular resource that is “spectrum”. In the contrary, inaccessibility to spectrum licenses is not the case in our discussions in section 6.3.2, since access to spectrum is not common across different actors of vertical layers9 . Power of customers is then yet another reason for horizontal coopetition where it also is considered a driver for vertical coopetition. But, considering Premises Owners as the customer in the case of indoor mobile network sharing, the force they burden on the MNOs to form joint ventures is far from the force SPs impose on the traditional actors of wireless ICT in “future telecom” value networks. In the latter case, the imposition causes changes in the positioning and strategies of firms in the business network, causing value networks to happen, but in the former case the burden is on whether to be present or not in a specific geo-location (or premises).

9 Spectrum

license holders are, in most cases, mobile network operators.

Chapter 8

Conclusions 8.1

Concluding Remarks

The main purpose of this study was to broaden the understanding of value creation process for the future telecom industry and highlight the role of telecom as a transformation tool for other industries. In order to do this we have focused on the relationships among firms that are involved in this process and discussed the two challenging relationships; Cooperation, and Competition. Hence we introduced three research questions in order to clarify the question of the title of thesis. The research questions are: RQ1 : Why do competitors in mobile service provisioning have to cooperate? RQ2 : Why do cooperators in mobile service provisioning compete? RQ3 : How would repositioning in the telecom value chain benefit traditional actors of telecommunication industry? The answers to these research questions were discussed in chapters 4, 5, 6, and 7. According to the discussions in section 7.3, the main findings are summarized below. RQ1 : Why do competitors in mobile service provisioning have to cooperate? We introduced the process of value co-creation in chapter 5 and section 2.2.3, and discussed the importance of co-creation when different ecosystems merge together. While convergence of industries and formation of value networks for future wireless ICT seem to be inevitable, the major cause of vertical cooperation can be co-creating value while still synergy, lack of resources and complementing competences are the forces driving this cause. We consider two instances of value 89

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CHAPTER 8. CONCLUSIONS

co-creation: a) Internal and b) external. If internal refers to where telecom actors, together, create the value and offer it to other industries, the external refers to a process that value is created among telecom actors and other industry actors. The former co-creation then represents transformation of ICT industry itself; and the latter represents instances of ICT transforming other industries. No matter the value creation is internal or external, in this thesis we argued that cooperation is inevitable and accordingly necessary; where its necessity is originated from the need for co-creating value. Hence, as the first research question investigated, the competitors would perceive the need for cooperating with each other due the mentioned reasons, although risks and uncertainties remain as major concerns (Figure 8.1).

Figure 8.1:

Co-creation of value in future telecom

8.1. CONCLUDING REMARKS

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RQ2 : Why do cooperators in mobile service provisioning compete? When cooperators see possibilities or reasons that content them to start competition with each other, a set of barriers (concerns) flaunt the actors of future telecom ecosystem. For the starter, the risk of hindering further “good” relationships with the cooperator is a big concern, whereas the uncertainties are diverse case by case. But at the same time drivers for starting the competition are high enough. Multiple examples show us that the complexity of relationships after starting competition with cooperator (in the market in general) does not stop firms from cooperating, rather they simplify the situation and “move on”. A viable example of this case is the ongoing situation in provisioning different sectors of IoT by MNOs and TEVs. It is obvious to all industries who are direct customers of “M2M/MTC enablement” that both MNOs and TEVs are offering service that facilitates their M2M/MTCenabled service offering. This means direct competition between MNOs and TEVs while at the same time these two groups are the cooperators in terms of creating another service for another customer, e.g. Mobile Broadband for end user. Accordingly, a prime reason for competing cooperators is creating a market that the cooperator is incapable of doing so; otherwise the entire market will be abused and heavy prices should be paid. The mentioned example of such vertical competition among TEVs and MNOs best exemplifies this situation where TEVs have found MNOs incapable of provisioning the (entire) IoT market, therefore decided to step in and avoid this big opportunity to be wasted. RQ3 : How would repositioning in the telecom value chain benefit traditional actors of telecommunication industry? While searching for instances of coopetition among actors of telecom industry, an interesting finding is that the convergence of wireless ICT actors and other industries for co-creating value in various industries has caused changes in telecom value chains. Hence we can refer to our arguments where we discussed that linear value chains cannot, any more, support the inter-firm relationships for future telecom. This is mainly due to the fact that value is not being created in linear chains anymore, but instead in value networks. At the same time diversity of markets that wireless ICT is involved with, simply creates a situation where telecom actors do not necessarily follow any “telecom-specific” patterns any more. As a result wireless ICT actors try to adapt to their Business customer’s preferences in their business to business (B2B) transactions, and customers’ respective market structure. This mix causes a web of relationships; instead of linear chains or simple networks. This argument overrules the third research question since the value chains are not viable any more. Instead, the traditional actors need to position themselves in places in the value network in a way that guarantees their presence among others as an important player; a player that brings a value that others cannot easily afford losing. This simply means that actors who tend to perform just traditional activities are replaceable, or in best case scenario they can reserve their existing businesses.

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CHAPTER 8. CONCLUSIONS

8.2

Future Work

In this thesis, we have looked into how the entrance of actors from other industries affects the telecom ecosystem. This dissertation then contributes to the study of vertical coopetition in ICT industry as well as the formation of value networks in the value co-creation process for wireless ICT. Since there is still a considerable room for improvement in studying the value-creation process, a mix of two angles for continuing this study is suggested: 1. Merger of telecom value networks and other industries value networks. 2. Platform thinking as the next step of value network. The first angle suggests that there is more to consider than just the presence of one actor (besides the telecom actors) when value is being co-created. Hence we predict this as the cause of new business relationships among traditional telecom actors and other involved actors in the newly created ecosystems. Samples of this merger have been already spotted in recent years. An instance of this merger is illustrated in Figure 8.2, where a long established advertising company in Amsterdam merges its value network with the telecom value network in order to co-create value for end users.

Figure 8.2:

An instance of merging advertisement value network and telecom value network

The second angle then suggests considering the formation of platforms in the value co-creation process. A platform “is a place where the producer and consumer share or exchange things without direct intervention by the platform owner” (Choudary, 2013). Platform thinking then is an approach in which by considering the role of end user tries to understand how creation of value and business interactions at inter-organizational level is changing. If we consider Smart City as the

8.2. FUTURE WORK

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platform for this study, since in platform thinking the role of end user is highlighted in process of value co-creation, the end user perspective and its effect on the ecosystems and positioning of firms can be considered. This directly relates to the hot topic of citizen engagement in smart cities.

Part II

Paper reprints

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Chapter 9

Shared Smallcell Networks Multi–operator or Third party solutions -or both? Jan Markendahl, Amirhossein Ghanbari In 11th International Symposium on Modeling & Optimization in Mobile, Ad Hoc & Wireless Networks (WiOpt) - Workshops (WiOpt - IOSC), pp. 41–48, IEEE, Tsukuba Science City, Japan, May 2013.

Fourth International Workshop on Indoor and Outdoor Small Cells 2013, May 13, 2013

Shared Smallcell Networks Multi-Operator or Third Party Solutions – Or Both? Jan Markendahl, Amirhossein Ghanbari Wireless@KTH, Royal Institute of Technology, Electrum 229, SE-16440, Kista, Sweden [email protected], [email protected] Most of the wireless data traffic is generated from indoor or local area locations. Examples are shopping malls, arenas, railway stations, trains, subways, hotels and office buildings where the users typically are employees of companies in the buildings. Facility owners do not want one single mobile operator to dominate the capacity provision. In the same way facility owners do not accept multiple physical indoor networks or infrastructures that need to be deployed and maintained by different actors requiring access to the local environment. Hence, a single shared infrastructure is of interest.

Abstract — Network sharing is a commonly used solution for macro cellular networks when mobile operators want to exploit benefits of sharing infrastructure, typically to save network costs. For local area and indoor networks infrastructure sharing using distributed antenna systems (DAS) and repeaters are commonly used solutions to improve indoor coverage. For these applications multi-operator solutions are well known and supported by both standardization bodies and by collaboration practices. However, when local networks are discussed in terms of femtocell solutions, offloading or heterogeneous networks, the multi-operator context seems to be forgotten. Small cells are often presented in a singleoperator context. This does not comply with market demand and practices, since facility owners neither want one single mobile operator to dominate the capacity provision nor accept multiple indoor infrastructures provided by multiple mobile operators.

In order to improve indoor coverage two types of solutions are widely used; Distributed Antenna Systems (DAS) [1] and repeaters. Here competing operators cooperate with each other and also with the facility owner and/or with companies using the indoor infrastructure. In this multi-operator settings the physical infrastructure i.e. the DAS network and the repeater equipment, is shared. However, the radio capacity (the base stations), the spectrum and the access control are managed by each operator. For pico- and femtocell networks the situation is different when it comes to sharing. There are multi-operator small cell solutions where both the base stations as well as spectrum and access control are part of the shared solution. In this paper we will discuss two main types of shared networks:

In this paper we will discuss the business model implications of different multi-operator solutions for indoor deployment. The key findings are in the areas of: i) how multi-operator small cell solutions can fit into existing market practices when it comes to operator business, ii) how local network operators (3rd parties) and outsourcing can play a role in the business landscape, and iii) how different (novel) spectrum allocation and access strategies can play a role for indoor network deployment. Keywords – Actors, business models, business roles, competition, cooperation, femtocell access points and gateways, indoor network deployment, MOCN, mobile broadband networks, offloading, network sharing, roaming, spectrum access, spectrum sharing strategies, techno-economic analysis, third party actors

I.

Multi-operator access to a local radio access network, operated by a local operator, by use of roaming Multi-operator access to a common radio access network enabled by gateway or multi-operator core network (MOCN) solutions

Introduction

For the technical solutions we will discuss the business model implications, the roles and responsibilities for different actors. We will especially look into the role of local network operators and 3rd part actors that can: i) operate networks on behalf of others, ii) offer capacity offload to mobile operators, or, iii) act as an independent local operator. Related to this we will discuss the business model options for outsourcing of deployment and operation of local networks.

The rapid increase of wireless Internet access services for smartphones, tablets and laptops has resulted in strongly growing demand for mobile broadband (MBB) access services. To meet the increasing demand more radio capacity needs to be deployed while at the same time controlling the increasing network costs in terms of both capital expenditure (CapEx) and operational expenditure (OpEx). For macro cellular networks sharing of base station sites and/or the radio equipment and spectrum are commonly used strategies to lower the network costs [1] [2] [3]. The benefits, drivers, drawbacks and risk with shared networks, with focus on macro cell networks, have been investigated in many papers, e.g. [4] [5] [6] and is quite well understood. However, network sharing for indoor and local area environments using small cell solution needs to be further researched. In this paper we will discuss sharing of small cell networks with focus on business model implications that can be identified for different technical network solutions

978-1-61284-824-2/2013 - Copyright is with IFIP

The paper is organized as follows: Section II describes related work and our contribution and section III outlines the methodology. In section IV business model options for the technical indoor solutions are discussed. Spectrum and capacity issues are discussed in sections V and VI. Business opportunities for outsourcing of local networks are discussed in section VII. Examples of business models are provided in section VIII using two case studies on local area networks. Conclusions are found in section IX.

41


II.

RELATED WORK AND CONTRIBUTION

B. Contribution Our techno-economic research on wireless indoor solutions targets three overlapping areas: network deployment, network sharing strategies and the role of trusted 3rd party actors. From the related work section we believe that there is a need to look more into indoor multi-operator solutions, both from a technical and a business perspective. We can identify three different problem areas with gaps in the current research:

A. Related work For heterogeneous networks joint operation of macrocells and pico/femtocell has been discussed in details [2]. Technical considerations and impairments of Femtocells and the tradeoff between coverage and capacity gains [3] are the other issues discussed in this area. Sharing networks have been discussed for outdoor networks focusing on resource sharing such as spectrum and site sharing [4] [5] [6] where viable business models based on them have been presented [7] [8].

Network sharing solutions for small cell networks Spectrum sharing and spectrum access strategies for local networks, possibly operated by local operators

When it comes to indoor networks, DAS approaches have been discussed for a long time [9] [10]. Local Wi-Fi and private networks have also been discussed [1], from which some business scenarios have been presented. On the other hand, ideas regarding sharing picocells as the indoor component of Heterogeneous Networks (HetNets) have been presented [11] where the focus is mainly on cooperation between different network layers [12]. How spectrum can be shared in the picocell layer is presented in [13] [11]. Regarding femtocell, manufacturers and MNOs have mainly discussed deployment of femtocells in their white papers from a single operator point of view, where deployed networks consist of home usage and so called residential femtocells [14]. Deploying residential femtocells for home and SOHO use from a single operator point of view are described in [14] [6]. Techno-economic analysis of indoor network deployment have recently been presented in [1] [15] [16] but multi-operator aspects are considered only in [1]. Regarding management and operation of indoor networks, a few studies on multi-actor public Wi-Fi networks have been conducted [17] that to some extent may be applicable to femtocell business models. Some discussions about profitability of femtocell deployments have been presented [18] [19].

Solutions for commercial small cell networks operated by actors other than mobile network operators When it comes to spectrum sharing and access strategies we can consider: i) use of licensed spectrum, unlicensed cellular spectrum bands (e.g. in the 1800MHz band) or some form of shared or secondary access. Related to the three problem areas above we have three main research questions: 1.

Can femtocell sharing solutions compete with DAS?

2.

What spectrum access options need to be exploited?

3.

What roles can local operators (3rd party actors) take? III.

METHODOLOGY

Due to the explorative nature of the research objectives a qualitative research approach has been used. A first round of interviews was conducted year 2010 and reported in [7]. Here Swedish mobile operators TeliaSonera, Tele2 and Telenor and telecom manufacturers Ericsson, Huawei and Nokia Siemens Networks (NSN) were interviewed about drivers and obstacles of network sharing in general. Interviews were also made about indoor deployment solutions and business models. In addition to the actors mentioned above, interviews were made with the Swedish and UK regulators (PTS, Ofcom), with equipment providers and system integrators (Absolute Mobile, MIC Nordic and Powerwave), with the Swedish real estate company “Jernhusen” and with big organizations using indoor solutions (the Swedish parliament and Uppsala University).

In addition, some assessment of outsourcing managed services for MNOs have been presented where economic issues of outsourcing were considered mostly by Frisanco [20]. Friedrich [21] presented brief insights into the motivation for network outsourcing and the rationale behind vendor selection from the operator perspective. Chaudhury [27] explained the risks and pitfalls that come with network outsourcing deals for network operators in their study, where they provide brief suggestions for the operators, in particular on what they can outsource and on what qualities in vendors that they need to look out for. Finally, Nunna [28] provides a status quo on the phenomenon of network outsourcing by proving an overview of the deals undertaken by major network vendors.

Year 2012 a second round of interviews was done with focus on indoor deployment, shared solutions and the role of third party actors. In addition to telecom manufacturers (Commscope, Ericsson and NEC) we interviewed companies with focus on local network solutions and services (Cloudberry, Icomera and MIC Nordic) and on management of networks of other actors (Ericsson Global Services and 3GNS). We also got valuable input from train companies in the UK and in Sweden (Keolis, SJ, SL and Transitio). The outcome of this second round of interviews is reported in this paper and in [35].

When it comes to spectrum allocation and different types of spectrum access solutions the growing mobile broad band traffic is a strong driver for different types of research. The need for and the benefits of additional spectrum have been discussed in [29] [30]. Different alternatives to allocation of more licensed spectrum are currently discussed, examples are secondary spectrum access, licensed/ authorized shared access (LSA/ASA) [31] [32] [33]. As Zander et al points out in [34] secondary access and LSA and ASA concepts are very interesting for indoor deployment due to low power levels and protection by wall penetration losses.

For analysis of the interaction between market actors we have used concepts and ideas from business network research [36] [37]. The ARA model was used to enable the mediation between technology and economic values. We complement this analysis by discussing the value proposition, the firm organization and value chain, and the position of the firm in the value network [38].

42


IV.

BUSINESS MODEL OPTIONS

In this section we will discuss business model options for multi-operator indoor networks using DAS and small cells solutions.

Operator Green’s Core NW

Internet

A. Distributed Antenna Systems DAS solutions are commonly used in a way to improve the indoor coverage for voice services. A DAS is a separate infrastructure with transmission and antenna elements where a base station dedicated for indoor users provides the capacity. Sometimes a base station that is shared between indoor and outdoor users provides the capacity of a DAS system.

Operator Red’s Core NW

Femtocell

Femto GW

Operator Blue’s Core NW Local cellular network With femtocell

Fig. 2 Multi-operator access using FeGW (the MOCN approach)

The DAS systems are divided into two main types, active and passive. The passive DAS is based on a distribution network based on coaxial cables and antennas. This type does not require any active electronics and is still favoured for smaller installations. In most cases active networks are now installed to match requirements on availability and performance. A DAS system itself is operator and often system independent which maintains the value of the deployment since it is geared to accommodate future standards and operators. A DAS system with multiple operators is shown in Fig. 2.

One form of multi-operator network is shown in in Fig 2. The radio access network involves FAPs and the FeGWs that manage the access points. In this case the operators share the same frequencies and the FeGW forwards to the traffic to the desired core network. This is one way to implement a multi operator core network (MOCN) solution commonly used for macro base stations [12]. Due to this feature the operators control their users and traffic, a potential problem is how the resources should be shared between operators..

In the business domain a DAS solution is fully transparent since each operator provides the capacity using own radio equipment and spectrum. An operator can independently provide more capacity to its own indoor users by upgrading the base station equipment. The indoor cells are part of the overall operator network, the base stations in the radio access network of each operator are connected to the respective core networks. From a business perspective this is business as usual for the mobile operators, the operators fully control their own cells and there are no potential problems when it comes to sharing of the radio resources. In this case the role of a third party actor can be to own and/or to maintain the indoor DAS infrastructure. The ownership of the DAS system does not have any implications when it comes to the end-users or the traffic.

With this solution the operators need to agree on what frequencies to use and how to deploy and operate the femtocell network. One mobile operator can deploy and operate the network making use of its own frequencies. Alternatively a third party can deploy and operate the femtocell network on behalf of the operators, still frequencies needs to be allocated for specific location. C. Multi-operator smallcells using dedicated frequencies A multi-operator femtocell network using different sets of frequencies for different subscriber groups are shown in Fig 3. Equipment manufacturers outline two ways to implement this multi-frequency feature: i) put two or more femtocells in to one “black box” or ii) put two (or more) chipsets in one femtocell device where each of them controls one dedicated frequency. With this approach the gateway should be located in the same premises in order to distinguish between different operator traffic and be able to send different streams of traffic over the internet. This is similar to the macrocell multi-operator RAN (MORAN) solutions that were presented after year 2000. For the operators this is very similar to the DAS approach since the traffic and frequencies are fully separated.

B. Multi-operator smallcells using common frequencies The femtocell networks include two types of nodes, the Femtocell Access Points (FAPs) and Femtocell Gateways (FeGW). The FAPs have built-in functionality for an adaptive and distributed radio management enabling self-configuration and self-optimization. The FAPs are connected to the operator core network using FeGWs and Internet connectivity. In section V we will discuss spectrum allocation for femtocells.



Base stations

Operator Green’s

Femto GW


DAS antenna

Operator Red’s Core NW Femtocell

Internet

DAS antenna Operator Red’s

DAS antenna

Local cellular network With femtocell

Operator Blue’s Core NW

DAS coverage


Operator Blue’s

Fig. 3 Multi-operator access using FeGW (MORAN approach)

Fig. 1 Distributed Antenna System

43


Agreements

Local Operator Core NW


Agreements

Premises Owner



Femto/Pico


Femto/Pico

Local cellular network With pico/femtocell



Fig. 4 Multi-operator access using local roaming

2) A local network operated by an independent actor For an actor without licensed spectrum the spectrum allocation is of crucial importance, no spectrum means no business. This is different to mobile operators that have spectrum and can face some planning or interference problems. The spectrum allocation options will be discussed in section V. For an independent local actor the main driver would be to enter an offloading business where capacity and access to indoor and local area networks are offered to mobile operators. A number of options exit for distribution of resources and roles between actors. The 3rd party actor running the indoor radio access network can acquire core network elements, a network code and an operator license and be an operator, see Fig 5. As an option the 3rd party can cooperate with some other operator already having these assets, this is illustrated in Fig 6.

1) A local network operated by a mobile operator A mobile operator has dedicated licensed spectrum and this would be the first choice. However, mobile operators tend to be unwilling to allocate separate frequency bands for exclusive use in indoor locations [7]. In addition, if the same frequencies are used for both macrocells and femtocells the operators are faced with network planning and interference challenges. An option could be to use unlicensed cellular bands, e.g. 1800 MHz, which have been allocated by some telecom regulators.

V.


SPECTRUM ALLOCATION AND ACCESS

For both mobile operators and 3rd party actor it is of interest to investigate alternatives to traditional licensed bands. Mobile operators want to avoid interference or to “waste” licensed bands and for 3rd party actors control of spectrum is a key to enter the business.

When it comes to business model options we believe that a mobile operator that deploys this type of local network enters a roaming business and where this effort is part of a cooperation strategy with other mobile operators. However, these types of activities require many and good relations with facility owners, something that may not be within the core business of typical mobile operators.

Agreements


Fig. 6 A local actor (e.g. a premisses owner) with a femtocell network cooperates with an operator with a core network.

D. Multi-operator access using roaming With a roaming approach we consider a mobile or local operator that deploys and operates a separate local network. Other operators and their subscribers can access the local network using local roaming, see Fig 4. This is similar to national roaming used by mobile operators and the terms and conditions for the usage require business agreements. Technically we denote this solution “roaming” but for the discussion of options for business models and frequency allocation we can identify two main cases depending on what actor that deploys and operates the local network: a traditional mobile operator or an independent (smaller or local) operator.

Premises Owner, a 3rd party


3rd part, MSP

The recent allocation of unlicensed bands in the 1800 MHz band in countries like UK, Sweden and the Netherlands enable any actor the possibility to offer GSM voice services in local environments. This offers the possibility to use cellular technology without any need to involve mobile operators. The GSM handsets are already available; another driver is that new smartphones will have LTE in the 1800 MHz band. For indoor and low power system another option is to exploit frequency bands allocated to other types of systems and applications. An example is broadcasting and the use of TV white spaces, i.e. TV channels not used at a specific location. Other examples are use of aeronautical bands just above 1 GHz and radar bands in the range 2.3-3.4 GHz [33] [34].



Femto/Pico


A key aspect here is that manufacturers of networks and user devices really will support the radio access technologies in these spectrum bands. The lack of manufacturer support is often mentioned as a major weakness for cognitive radio and secondary spectrum access solutions. However, more long term, investment friendly and less risky approaches like LSA are currently discussed [32].


Fig. 5 A local actor (e.g. a premisses owner) with a femtocell network acquring a core network becoming “an operator”

44


Another important aspect of spectrum allocation is the coexistence of macro and femto/picocll layers. One well know example for closed access femtocells are the coverage holes that appear around femtocells for devices connected to distant macro base stations using the same or adjacent channel [7]. Standalone bands dedicated for small cell use hence would imply two type of benefits to mobile operators: i) avoidance of interference with macrocells and ii) bands below 3GHz can be used for wide area macrocell deployment. Hence, roaming or 3rd party indoor solutions not using licensed operator spectrum will provide additional benefits to mobile operators. VI.

VII. OUTSOURCING AND THE ROLE OF 3RD PARTY ACTORS The operation and management of each indoor network, based on the used sharing model, can be either done by the operator itself or an authoritative outsourcee. In some models it is quite more relevant to outsource O&M to one singular outsourcee. For instance, in case of MOCN sharing, since the FeGW is located at the customer’s premises and shared among different operators, it is more admissible to operate the network by one singular outsourcee who controls the existing Smallcell network and FeGWs. Another case of outsourcing O&M in Smallcell networks can be in implementing comprehensive systems. In case of such a wholesale sharing approach, it is the authoritative third party that is acting as a full outsourcee of network operation and management for respective MNOs.

CAPACITY COMPARISON

Another aspect of shared indoor networks and the choice between DAS and small cell solutions to consider is capacity. DAS systems have the capacity of macro base stations and small cell solutions with many nodes provide a very high capacity. This can be illustrated by a capacity-demand analysis where we compare the number users that can be served [42].

It can be depicted that the Operational Expenditure of an indoor network could be broken down typically as listed below, of which Customer Relations (customer acquisition, customer retention and customer services) enfolds the biggest portion, at the same time Network OpEx embraces a bigger effect on operator’s policies.

Assume that the indoor users consume 10 GB per month today and will consumer 50GB in the “future”. The data is consumed during 8 hours of the day (all equally busy) during 30 days. This corresponds roughly to average bit rates 0,1 and 0,5 Mbps, note that this is average number used for capacity estimates. We consider small cells using 5 or 20 MHz of spectrum and DAS systems using 20 MHz of spectrum. In order to do a sensitivity analysis in the dimensions demand, allocated spectrum and deployment strategies we also vary the spectral efficiency and use the values 1 and 10 bps per Hz. This can be compared to the 3GPP and ITU target values of 1530 for the peak values and around 2 for the cell averages. In an indoor environment the spectral efficiency will be well above 1 bps per Hz. The values in table I indicate that the following number of users can be served per node

• • • •

The operational costs represented as IT costs are the IT functions of the company which are mainly administrative and not much related to network operations. On the other hand, the second valid option would be outsourcing Network Operation by accepting the change in business landscape described earlier. Regardless of the cost structure of any mobile operator, either a MNO or a MVNO, the most expensive segment of the expenditures for any Smallcell network would be customer relations, considering that CapEx is relatively quite low for Smallcell networks. Therefore, this situation makes the business models complex for network operators in terms of gaining revenue at the same time handling costs. As a result, companies need to focus more on their core business and try to lessen the burdens brought by technical functions.

50 – 500 10GB users or 10-100 50GB users with a 5 MHz femtocell 200-2000 10GB users or 40-400 50GB users with a 20 MHz picocell or DAS system This sensitivity analysis has two major implications. First, the small cell solutions provide very high capacity; the indoor systems will not be capacity limited. Sharing of small cells is perfectly OK from a capacity perspective.

Two major groups can be mentioned as valid outsourcee’s: telecom network vendors and independent 3rd party actors. A. Telecom network vendors The first group that already acts as MSP for network operators in case of macrocell networks around the globe is telecom network vendors like Ericsson and Nokia Siemens Networks. Since these companies are the specialists in developing and manufacturing specialized telecommunication devices, they better know how to manage them technically in the most efficient way. It should also be added that MNOs also trust their networks’ infrastructure supplier when it comes to outsourcing the same networks’ operation. The second candidate then would be a company with fewer resources than infrastructure vendors, in terms of specialization in manufacturing equipment, but at the same time enough O&M capabilities as well as some connections. Less complexity of their business models as well as higher efficiency due to simplicity of their organizations in comparison to the first group is an advantage for this group.

Secondly, the DAS systems will have capacity limitations, especially for future “high” demand levels. In large buildings there will more than 40-400 users. However, a DAS system can be “sectorized”, e.g. by deploying one “sector” per floor. TABLE I COMPARISON OF (THEORETICAL) NUMBER OF SERVED USERS System bandwidth (MHz)

Spectral efficiency (bps / Hz)

System Capacity (Mbps)

No. served 10GB users

No. served 50GB users

5

10

50

500

100

5

1.0

5

50

10

20

10

200

2000

400

20

1.0

20

200

40

Network OpEx Customer Relations (CR) Interconnect IT

45


B. Multi-operator access using roaming Some actors deploy local radio access networks and offer this as a service to mobile operators, this is called Small Cell as a Service (SCaaS) and is illustrated in Fig. 5. SCaaS is an emerging model that allows third parties to roll out a Smallcell network and then rent it to several operators thereby lowering the barrier to entry for deployment and total costs [43].

VIII. CASE STUDIES A. CloudBerry Mobile: better coverage & offloading capacity Indoor networks could be implemented to help operators overcome cost and capacity challenges for mobile operators by offloading data from macrocell networks to smaller available cells for indoor users.

In this field, over the second quarter 2012, Virgin Media announced it is trialing LTE small cells in the UK ahead of launching its Small Cell as a Service offering and Colt Telecom announced it is already in trials with a major European operator. Furthermore, two new companies Cloudberry Mobile and ClearSky have launched their own offerings in Europe and the US, respectively, targeting smaller operators. Without deploying large numbers of Smallcells the mobile network simply could not sustain the continued growth in data usage. Such a dramatic network transformation opens up interesting new. It allows third parties to build networks that several mobile operators can use, thereby reducing costs and time to market. At the moment, this is being targeted at major operators that are looking for a simple route to establish a small-cell network as well as smaller players that have found the barriers to entry too much to enter.

Cloudberry is a startup company that provides small cells to consumers and enterprises in Norway. It provides mobile coverage and capacity where the customer needs it. Cloudberry is the first small cells operator in the world which is using its experience to provide small cells services wholesale to other mobile operators in Europe and elsewhere1. Cloudberry targets the smaller network operators in European countries, typically the 3rd or 4th, who do not have such large network assets as their larger competitors. Cloudberry’s solution may also be attractive to some MVNOs

C. Example of an indoor mobile network ecosystem An example of actors and relations for provisioning of Small Cell as a Service (SCaaS) is shown in Fig.7. In this model the MSP is the main actor in the ecosystem playing all the major parts. MSP deploys and operates the network on behalf of any MNO/JV trying to enhance the quality of their network by expanding the coverage as well as increasing the capacity of the their overall network. This is done by means of densification of the network by deploying femtocells indoors. The MSP also takes care of the relations needed with the premises owner on one hand and the relations with NW vendors during the supply chain on the other hand. There might be some business relations needed between premises owner and the MNO/JV in the initial steps in regard to bind some needed agreements but since the main procedure is through the operational period it can be avoided in the scheme.

B. Onboard train solutions According to the UK regulator “Ofcom” technical problems of the so called "not spots" onboard trains are explained as a combination of mobile network coverage problems and attenuation of the signals inside the train carriages. Commercial challenges are said to arise from “lack of immediate benefits to the major mobile network operators to extend good coverage along the full length of all rail routes and lack of financial incentives on the train operating companies to implement physical enhancements to their trains to enable better signal delivery for voice signals. This is from a UK perspective where for Sweden the situation is slightly different.

Cloudberry offers Small Cell as a Service, where a Smallcell gateway (FeGW) is hosted and all the logistics of rolling out residential and enterprise femtocells are remotely operated. The Cloudberry case is illustrated in Fig. 5. In cooperation with a single mobile operator the frequencies of that operator is used.

For repeater systems the Swedish operators join forces and deploy a common onboard system where costs are shared, hence it is not the train operators that make the investments. Another difference is that Swedish operators usually agree on a common onboard system whereas UK and German operators deploy single operator systems onboard trains as part of cooperation with the train company. The possibility to use unlicensed 1800 MHz band for an onboard local train network for voice services has been identified. This local network can be seen as a "moving cell" where the connectivity to the train is provided by multiple cellular links using 3G and/or 4G technology [8]. This is the same approach that has been used for years where an onboard local Wi-Fi network provides data services. The local network can be provided by the “facility owner”, i.e. the train company. The mobile operators can access the onboard train system using roaming. The train company can be “a local operator” according to Fig 6 or cooperate with another operator as illustrated in Fig 7.

Fig. 7 Example of actors and relations for outsourcing of operation and maintanance in Smallcell networks

1

46

Exclusive interview with Geir O. Jenssen, CTO Cloudberry Mobile


IX.

Eventually, since small cells can satisfy required indoor capacity, if operators dedicate a specific part of their bandwidth to their small cells they can avoid interference to a considerable extent by avoiding co-channel operation but still the likelihood of some interference is conceivable due to adjacent channel operation. But it is still negotiable that operators mainly do not tend to “waste” the frequency in this form. As a result, the proposed MOCN sharing model would exploit interference avoidance by stacking up enough bandwidth for deploying shared smallcell networks by contribution of all participating MNOs. On the other hand, Roaming also enhance interference avoidance since a different frequency, compared to operator’s original frequency for macrocells, is being utilized. Where it also highlights the presence of a local operator that only deploys smallcell networks and lease coverage and capacity (on demand) to existing MNOs and can facilitate the situation by using its own frequency (either licensed or unlicensed). This concept is a major driver for the wholesale sharing approach introduced by a full network O&M outsourcee (wholesale sharing), discussed in section VII.

CONCLUSIONS

Most of the wireless data traffic is generated from indoor or local area locations like shopping malls, arenas, railway stations, trains, subways, hotels and office buildings. Here, shared local networks are highly interesting. Facility owners neither want one single mobile operator to have a local monopoly nor that multiple physical indoor infrastructures to be deployed. For indoor networks infrastructure sharing using distributed antenna systems (DAS) and repeaters are commonly used. The same is true for sharing of macrocell networks. For these cases multi-operator solutions are supported by both standardization bodies and by collaboration practices. However, when local networks are discussed in terms of femtocell solutions, offloading or heterogeneous networks, the multi-operator context seems to be forgotten. Small cells are often presented in a single-operator context. This lead to the first research question addressed in this paper: Can femtocell sharing solutions compete with DAS? Small cell solutions have cost and capacity advantages [7][21] so why are operators hesitant to use these solutions? One reason may be that operators may see a risk to lose control of its own users and traffic. For the cases of network sharing of macrocells, DAS systems and repeaters the radio capacity (the base stations), the spectrum and the access control are (or can be) clearly managed by each operator. We believe that the control aspect is important to consider on order to get operators more interested in shared smallcell networks.

REFERENCES

For both mobile operators and 3rd party actor it is of interest to investigate alternatives to licensed bands. Mobile operators want to avoid interference with macrocells or to “waste” licensed bands and for 3rd party actors control of spectrum is a key to enter the business. This leads to the second question: What spectrum access options need to be exploited? In the short term the use of unlicensed 1800 MHz bands for GSM and LTE should be investigated. Is the allocated bandwidths (5 MHz or less) enough for efficient deployment. In the long term the possibility to use special indoor bands, either exclusively or using shared access, should be analyzed. Here shared access with radar bands above 2GHz is an interesting option. The last research question addresses technical and business solutions for commercial small cell networks operated by actors other than traditional mobile network operators: What roles can local operators (3rd party actors) take? Owners of office buildings, shopping malls, etc. and transportation companies can exploit the control of the local environment (and the users). These actors can exploit their position by either deploy and operate a local network by themselves or by letting a third do this. In both cases the local network can either be part of mobile operator networks (DAS; MOCN or MORAN approaches) of the local network can be accessed using roaming. In the latter case the local operator need to acquire core network nodes and a network codes and act as an operator, or to cooperate with an operator with these resources and assets. We have also identified the new concept “smallcell as a service” where 3rd party actors offer capacity and offloading to traditional mobile operators.

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[23] M. R. Head, A. Sailer, H. Shaikh and M. Viswanathan, "Taking IT Management Services to a Cloud," in IEEE International Conference on Cloud Computing (CLOUD '09), 2009. [24] P. A. Laplante, T. Costello and M. London, "The who, what, why, where, and when of IT outsourcing," IT Professional magazine, vol. 6, no. 1, pp. 19-23, 2004. [25] T. Frisanco, "Strategic and Economic Benefits of Regionalization, Centralization, and Outsourcing of Mobile Network Operations Processes," in Fifth International Conference on Wireless and Mobile Communications, 2009, 2009. [26] R. Friedrich, P. Weichsel, J. Miles and A. Rajvanshi, "Outsourcing Network Operations - Maximizing the Potential," Booz&co. Business Report, Germany, 2009. [27] R. Chaudhury and C. Terfloth, "The Lure of Network Outsourcing – Promise and Pitfalls for Telecom Operators," in Annual Review of Communications, Chicago, International Engineering Consortium, 2009, pp. 67-74. [28] S. Nunna, R. Ermecke and D. Schupke, "Toward Modeling Rationalization Potential in Network Operations and Maintenance Outsourcing," in International Conference on Communications Workshops (ICC), 2011. [29] J. Zander and P. Mähönen, "Riding the Data Tsunami in the Cloud Myths and Challenges in future wireless access," to appear in Communications Magazine, 2013. [30] FFC , "Mobile Broadband - Benefits of Additional Spectrum," White Paper, 2010. [31] S. Forge, R. Horvitz and C. Blackman, Perspectives on the value of shared spectrum access, final report for the European Commission, SCF Associates, 2012. [32] P. L. Parcu and e. al, Authorised Shared Access (ASA) - An Innovative Model of Pro-competitive Spectrum Management, available at: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2174518, 2011. [33] L. Simic, M. Petrova and P. Mähonen, "Wi-Fi, But Not on Steroids: Performance Analysis of a Wi-Fi-Like Network Operating in TVWS Under Realistic Conditions," in IEEE International Conference on Communication, 2012. [34] J. Zander and e. al, "On the Scalability of Cognitive Radio: Assessing the commercial viability of secondary spectrum access," to appear in IEEE Wireless Communications Magazine, 2013. [35] A. Ghanbari, Indoor Multi-operator Solutions - Network sharing and Outsourcing network management and operation, Stockholm: MSc

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Chapter 10

Tele-Economics in MTC: what numbers would not show Andrés Laya, Amirhossein Ghanbari, Jan Markendahl1 In the EAI Endorsed Transactions on Internet of Things, vol. 1, pp. 1–12, October. 2015.

EAI Endorsed Transactions on Internet of Things

Research Article

Tele-Economics in MTC: what numbers would not show Andres Laya1,*, Amirhossein Ghanbari1 and Jan Markendahl1 1KTH Royal Institute of Technology. Communication Systems (CoS) department. Kista, Sweden.

Abstract This paper elaborates on the relevance of Tele-Economic research to understand the effect that Machine-Type Communications (MTC) has on different markets and also the market forces affecting the adoption of services based on MTC. The paper is presented in a tutorial form, offering concept and definitions of economic terms that are gaining relevance in the technical community in the MTC context. The concept of services is further analysed in as a change in the telecommunication industry mind-set in order to tap into the economic value of MTC in the realization of the Internet-ofThings. Finally, insights are presented looking forward into the relevance of Tele-Economic research for 5G. Keywords: Tele-Economic research, service enablement, Machine Type Communication, Internet-of-Things. Received on 06 October 2015; accepted on 21 October 2015; published on 26 October 2015 Copyright © 2015 A. Laya et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. doi: 10.4108/ eai.26-10-2015.150596

1. Introduction

approach to extend the connectivity provisioning into connectivity services that include usage monitoring, support of fault resolution, and some level of service enablement to support application developments. J. Morrish [1] makes an important contribution by suggesting that this connectivity between devices is not about a technical solutions; it is more about the applications benefiting from this connectivity. These benefits might be related to improving old functions or performing new functions. In this respect, it is difficult to discuss in terms of a MTC market, since it is a set of technologies with supporting capabilities across different markets [1]. So, the fact that MTC is about supporting something highlights the need of research and development on the values and possibilities in specific areas. We could argue that MTC first took off within the telecom industry, and has been widely promoted by it ever since. And it is precisely for this reason that the benefits and potential are clearer on the technology side than on the application (market) side. Many of the possibilities and concepts are rather abstract and mainly understood inside the ICT community. Even if there is an increasing interest in the consumer or societal impact, it has become essential for the technical community to find well-grounded evi-

The opportunities that Information and Communication Technologies (ICT) offer to any industry considering the transformation of products and places into smart, connected system have stimulated academics and professionals from every discipline to explore and collaborate in concrete realizations of this vision. This paper elaborates on the relevance of considering research from different disciplines regarding this emergent communication enablement trend. † MTC is a topic commonly discussed to provide of additional streams of revenues for mobile operators as one way to narrow the mobile revenue gap. Consequently, it is natural to see the appearance of enablement platforms as an †

Machine-to-Machine (M2M) is usually referred to as the communication between remote machines and central management applications. Similarly, Machine-Type Communications (MTC) implies the communication where at least one element is a Machine. Since it is the working terminology used by 3GPP, MTC it is often regarded as the segment of M2M carried over cellular networks. *

Corresponding author e-mail: [email protected]

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dence of the benefit that can be attained with MTC. Hence, the objective of this paper is to present how Tele-Economic research can support this goal. Before presenting details on the meaning and scope of Tele-Economic research, let us reflect on the relevance of techno-economic modelling. The purpose of these models is to have supporting insights to steer a technology development into a market-feasible solution. Techno-economic modelling proved the relevance in the telecommunication sector with the development of frameworks and tools to study possible network development or migration paths [2], taking into account costs and revenue models of technology and user adoption. An instance of this standpoint is given in Telenor R&I review on the chronology of telecommunication research projects and programs using technoeconomic methodologies [3]; starting with deployment models for the access networks, followed up by research

related to business models, demand forecasts, costs models and sensitivity and risk assessments. There is a vision that techno-economic studies are merely a new dimension of performance boundaries to narrow scientific development within economic performance metrics. The underlying aim of this paper is to show the potential and status of Tele-Economic research as complementing methods to enhance, direct and exploit the technology possibilities; by understand the market context where the technology is applied. The driver for Tele-Economic research in MTC is to find and understand the real value and potential benefits of MTC communications, beyond the communication layers; in order to do so, we discuss in terms of the service enablement capabilities of MTC for solutions based on connected devices.

Figure 1. In mobile broadband, the business is discussed in terms of connectivity; the most relevant actor corresponds to connectivity providers (carriers). In MTC the business is discussed in terms of the service that it is enabled on top of the connectivity, hence, the most relevant actor is the service provider.

seems to be a common interest from the major maker players to position themselves as enablers of services based on MTC to tap into the economic value of the future vision on the Internet-of-Things. Naturally, this reconfiguration is resulting in closer discussions with non-ICT industries and, since MTC is about enabling services for other industries, input and discussions are merging from different angles. Some economic concepts and terms are gaining relevance in the technical community and it is worth clarifying their origins, usage and relevant in the MTC context. But does not all that research belong somewhere else? It might seem so, but closer collaboration from different disciplines would benefit from a common level of understanding. Moreover, we see the increasing attention that funding research bodies are giving to interdisciplinary studies. This focus brings a challenge in language differentiation. Instances of notions from industrial management and economic research are closely influ-

On Figure 1 we make a simplified mapping of the actors in the telecom sector to compare the focus on connectivity for mobile broadband services and the focus on services on top of the connectivity provision. When the discussion is on a connectivity-oriented context, the main players interacting with the final user are the mobile operators (or carriers); this constitutes the traditional organization of the telecommunication sector. On the contrary, the right-hand side of the figure represent the discussion in terms of the services provided on top of the connectivity, where the pivotal players are those firms providing value added services, such as over-the-top players. In this case, even if the communication is a fundamental enabler for the service, the involvement of mobile operators is many times described just as the providers of the data transport infrastructure. MTC has boost a reconfiguration of the telecommunication industry, which is on an early stage and there are only predictions of the future panorama, however, there 2


Tele-Economics in MTC: what numbers would not show

encing technology research. We aim at providing comprehensive material on some of these aspects to a technical audience in order to tutor on the meaning and scope of Tele-Economic research regarding recent and forthcoming challenges in MTC. The paper is discursive and a tutorial in nature. The remainder of the paper is organized as follows: on the next section we present concepts and definitions with key references related to the service enablement. This is done, mainly, in order to familiarize the reader with the concepts used in the later discussions. Afterward, we discuss the relevance of Tele-Economic research for MTC, with strong focus on the service enablement. We continue with a section dedicate to the implications towards 5G research regarding MTC, highlight current technical considerations that are built on top of the service enablement mind-set.

[14] to describe a “world of seamless connected devices that would save us time and money”, based on the interconnection of the physical world with the virtual world of Internet [15]. In short, we argue that M2M—and MTC— are communication enablers for the broader concept of the IoT. Recently, there has been yet another term with similar connotations; Cellular IoT—or CIoT—is a terminology used to denote IoT networks operating in licensed spectrum [16].

2.2. Techno-Economics The term Techno-Economics does not count with a strict definition and it suggests different meanings depending on the context. Back in 1990, sociologist Michael Callon [17] introduced the concept of Techno-Economic Networks (TEN) as a solution to describe and analyse the interactions between actors influencing technology development; linking social and economic notions and arguing that actors define one another in interaction, by means of the intermediaries that they put into circulation. Perez [18] and Freeman [19] present the notion of Techno-Economic Paradigms (TEP) as a solution to describe and analyse the relation between long-term fluctuations in economic growth and the links with major technical changes [20]. Comparing these two notions, Green et al. [20] argue that TEN literature is focused on describing the emergence and stabilisation of technology, while TEP literature is focused on challenges related to diffusion of pervasive technologies. By analysing these broad perspectives, we infer that Techno-Economics correspond to interdisciplinary efforts that consider social, economic and regulatory aspects to analyse the effect of technology innovation or intervene in its development. As a result, from a commercial point of view, this interdisciplinary field complements pure technological research to break the assumption that any technology development will eventually result in new commercial products or processes [20]. It is, therefore, a group of approaches dedicated to the “linkages between technological, economic and social change” [21].

2. Concepts and Definitions The purpose of this section is to present concepts and definitions of common terminology that tends to be misapplied and, at times, abused. It is the most tutoring section of this manuscript, giving a necessary literature review on the multi-disciplinary context of this work.

2.1. M2M, MTC and IoT Three terms, Machine-to-Machine (M2M), MachineType Communications (MTC) and Internet-of-Things (IoT); they entail complementing concepts but are often used interchangeably. They all imply the notion of connected autonomous devices, but we delimit them— based on literature comparison—as presented next. M2M has an accepted definition as the set of wireless and wired communication between mechanical or electric devices [4] or, as presented by Whitehead in 2004, communication between remote machines and central management applications [5]. Anton-Haro and Dohler [6] extend the concept and include all the information and communication technologies able to measure, deliver, process and react upon information in an autonomous fashion. M2M and MTC are at times considered synonyms [7] [8], however, since MTC is the working terminology used by 3GPP, it is often regarded as the segment of M2M carried over cellular networks [9] [10]. These two are telecom terms and therefore they have a strong focus on the network side [11]. When it comes to IoT, Höller et al. [12] describe it as a set of technologies, principles and systems associated to Internet-connected objects, coinciding with the EIRC and ITU-T definition [13]. Clarifying that, in contrast to M2M, IoT includes the connection and access to the broader Internet. The term was first coined in 1999 by K. Ashton

2.3. Tele-Economics Tele-Economics is a line of research on telecommunications that applies economic research approaches on the knowledge from the technology research. The purpose is to understand the effect that technology development has on different markets and also the market forces affecting the evolution of the telecommunication industry. Tele-Economics includes topics such as the study of the behaviour of the telecommunication market, the organizations within this market, the customers and

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users. It also includes the analysis of costs and benefits, and the interactions and relationships among different actors, and analysis of operations.

and economic space to find novel methods to benefit from a technology. This stage is not related to technical development and is more focused on regulation and market structures including demand analysis, analysis of value and behaviour models for pricing. Additionally, it involves topics regarding the relationship between the service / network provider and users, analysis of the business models and cost structure analysis and the impact of regulation and licensing. Lastly, strategic decisionmaking by means of game theory methods falls within this stage. The illustrated approach in Figure 2 can start from any of the four corners based on the fact that the research is demanded by the market or pushed by the technology. The important consideration is that the stages on either side (left/right) have closer interaction to each other and benefits from repeated cycles, providing input for further researcher before passing to the other side.

Figure 2. Tele-Economics described as telecommunications and economics research interactions.

On Figure 2 we present a descriptive interaction between the two general disciplines, Telecommunications and Economics, highlighting four main stages. The two stages on the left represent demand from the market, which are considered market Pull. This market then corresponds to any market where Telecommunications can play a role or even Telecommunications market thereof. On the right side, the two stages represent the supply for market, which are the technology push (consider all ICTs). The stages Tele-Economics focus on: Needs in technology: corresponds to research showing clear demand in the market for new technology. Findings relate to identification of gaps in the market for technology solutions. Technology development and maturation: corresponds to the more technical stage in the interaction. In this stage a technology is either developed or enhanced. The aim of this stage is twofold: • If this stage is the departure research point, a new technology is developed and is then passed on to viability study. • If this stage has been reached after finding a need in the market. The gap drives the telecom industry to come up with a technique to address the demand. Viability of technology: corresponds to analysis and performance evaluation of certain technology. This stage is related to work on deployment studies, and cost calculations applied to telecommunications. The relationship between different types of providers of networks and services including construction, operation and maintenance of infrastructure, the infrastructure requirements of services and users, marketing organization for the provision of networks and services and the interaction between technical solutions and on the other hand, market mechanisms, regulation and competition law. Innovation in the approach of using the technology: corresponds to research and innovation in the market

2.4. Value, Value Chains and Value Networks Value is another terminology with many interpretations with often appearance in research and discussion environments. McQueen and Dobb [22] described value, in economics, as worth of a commodity in terms of other commodities, or in terms of money. Michael Porter [23] defined value as what buyers are willing to pay for products or services. In the context of our research, we define value as a measure of the benefit provided by a good or service to an actor, where, according to Keen [24] it is generally measured relative to units of currency. Michael Porter first introduced the term Value Chain in 1985 [23] as the interrelated operating activities, which businesses perform, during the process of converting raw materials into finished products. The terminology since then has evolved and been put into different contexts. In 2001 Kaplinsky and Morris [25] defined value chain as a tool to describe economic activities that are required to bring a product or service from conception to final consumers. As presented in Figure 3, within the traditional vision of value chains, value in created in consecutive steps by activities that add value to the final product or service. Normann and Ramirez [26] present a change in the perception of the value chain, by suggesting that it is no longer possible to define fixed positions for firms based on a set of activities along a value chain. Instead, they refer to the value constellations, or value networks, as a model to focus on the overall system, with focus on the value creation. The general difference in the concepts of value chains and value networks is presented in Figure 3.

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Tele-Economics in MTC: what numbers would not show

2.6. Business Ecosystem This term is commonly used in the literature and finds a concrete definition in J.F. Moore’s work [35] as “the network of buyers, suppliers and makers of related products or services” within a socio-economic environment that includes institutional and regulatory frameworks [15]. Furthermore, Mazhelis et al. [15] and Iansiti and Levien [36] argue that a business ecosystem evolve around a specific core, which corresponds to shared and common assets. Common assets could be presented in the form of platforms, technologies, processes, and standards that are fundamental in their businesses. Also in [15], the authors consider IoT as a particular business ecosystem. They partake on the definition of IoT Ecosystems by considering a core composed of hardware and software products. These products then focus on connected devices, the connectivity itself, the solutions built on top of this connectivity, and the supporting activities of such solutions. Figure 3. General representation showing the concepts of value chains and value networks

2.7. Services According to Vargo et al. [37] a “service is the application of competences (knowledge and skills) by one entity for the benefit of another”. This definition implies that value is created based on the interactive exchange between entities [38] [39]. The reason to present and discuss this term is to emphasize the fundamental shift from economic exchange based on goods towards markets dominated by the provision on services. They refer to this new mind-set shift as the Service-Dominant Logic. Leveraging on the “research manifesto for services science” by Chesbrough and Spohrer [40], it is possible to appreciate that services share essential elements, and we highlight the following common elements of services enabled by ICT: services by nature cause a close interaction of supplier and customer; they result from a combination of knowledge into useful systems; finally, they are characterized by the simultaneity of production and consumption of value [40] [41]. According to Lusch and Vargo [38], in the ServiceDominant logic, customers become co-creators of values, underlining the relevance of the interchanges in the relation between customers and suppliers. A distinctive quality of Service-Dominant logic is that it considers customers, employees and organizations as dynamic resources; denoting that all parties are simultaneously creators and beneficiaries of values. We should make a distinction between the meanings of the term service between economics and computer science. For example, Thoma et al. present a technical survey on computer science where they identify services as one of the main building blocks of the IoT [42]. They present a definition of the term IoT-Service as “a transac-

2.5. Business Models As Morris et al. [27] believe, there is no commonly accepted definition for the term “Business Model,” Nevertheless, it is commonly used. Different scholars tend to focus on different approaches while describing the term, which is mainly because they believe different issues are more important in the description [28]. Basically, Stewart and Zhao [29] consider Business Model “a statement of how a firm will make money and sustain its profit stream over time.” Elaborating more on the details of constituent elements of a business model, Morris et al. [27] believe that “A business model is a concise representation of how an interrelated set of decision variables in the areas of venture strategy, architecture, and economics are addressed to create sustainable competitive advantage in defined markets”. The competitive advantage then is translated to creating value by Osterwalder et al. [30] within the so-called Business Model Ontology (BMO). They believe that a business model should express the logics of a specific firm describing “the value a company offers to one or several segments of customers and of the architecture of the firm and its network of partners for creating, marketing, and delivering this value and relationship capital, to generate profitable and sustainable revenue streams”. There are several complementing academic resources that discuss and consider the following concepts of business models: value proposition, cost structure, profit potential, value chain, competitive strategy, value network, business model innovation, the actors, resources and activities [31] [32] [33] [34].

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tion between two parties, the service provider and the service consumer. It causes a prescribed function enabling the interaction with the physical world by measuring the state of entities or by initiating actions which will cause a change to the entities.” [42]. This definition limits the notion of service to computing functionalities and does not capture the aforementioned notions the service-dominant logic. Therefore, when making reference to MTC and the transformation of markets based on connected devices, it is more appropriate to refer to IoTenabled service; on the prerequisite that such service relies on the availability of M2M or MTC.

tions [28] [44] . This matter has been explored by academics and the transformation from product to service to tap into the MTC value is gaining a strong momentum, as we present in the following section.

3.1. MTC and Services As presented in Figure 4, when addressing MTC there should be a consideration of the shift from products to services. Instead of focusing on the development of MTC products and understand their value, the focus should be on the creation of experiences and co-creation of value. Heapy [45] elaborates on this topic from a service design perspective, reasoning that value should be created through use, exploring beyond the point of sale. In this sense, MTC devices and networks are clearly positioned as value enablers in the IoT context. As described by Berkers et al. [46], the evolution of service based on connected devices have parallels with earlier telecom advances, which first integrated richer value-added services and then evolved into service delivery platforms that simplified the management and creation new services. A similar service creation enablement trend is evolving around MTC towards IoT-enabled services [46].

3. The relevance of Tele-Economic research for MTC Since MTC is regarded as an enabling technology, the purpose of performing Tele-Economic research on MTC is to analyse the context in which the technology is being used or might be of use. Therefore, Tele-economic research on MTC is not restricted to connectivity and deployment aspects. It can be used to differentiate barriers related to the lack of adequate technology from barrier associated to inconvenient business and market settings. Understanding these differences helps in channelling efforts to overcome diverse barriers, either by focusing on technology refinement or by finding and suggesting adequate changes in the business or market settings. MTC is maturing, but even with a general industry growth there is a challenge in the understanding of the benefits that MTC could bring in different industries. Big corporations get the main message but much more focus ‡ should be on the costumers and their needs . It is important to make sure to get the best technology for each case but, when considering the transformation that MTC brings into a product or solution, the communication aspects are not generally a concern on the customer’s § side; they are just a fraction of the overall problem . Our previous findings when examining different cases suggest that it is simpler to analyse the values and benefits of stand-alone solutions [43] but considering complex cases, such as Smart Cities, makes difficult the tasks of understanding what the values and benefits are. Besides, even if intangible values are elucidated—such as efficient resource management, optimized working times or continuous interaction with customers and users—the tangible economic benefits are yet unclear in many applica-

Figure 3. Change from product to service oriented solutions and offers.

Notably, MTC is about connected devices and therefore, at this stage, it is difficult to discuss in terms of a transformation from product to services; it is more suitable to discuss in terms of combination of products and services. In this sense, Product-Service System (PSS) “is a concept for business to improve their sustainability performance. The approach analyses the needs of consumers to be filled by products and services, and uses results as a basis for innovation” [47]. PSS covers the combined offering of products and services, instead of a sole focus on products [48]. Elfving and Urquhart [49] describe how telecommunication industry has been on a transition state toward a service focus on their business in recent years. Based on that, MTC can be considered an enabler of “smart products” and a driving force propagating the product-to-service transition to other industries.

‡

Insights from an interview to the Chief Marketing Officer in a M2M Global Managed Service Provider firm. § Panel intervention at the 2015 Johannesberg summit from the Global R&D Program Manager in a multinational engineering firm.

**

The challenge related to not knowing where the value is and how to capture it was highlighted during the Enabling transformation by embedding intelligence keynote at the Ericsson Research Open Day 2015.

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Tele-Economics in MTC: what numbers would not show As explained by Elfving and Urquhart in [50], PSS has evolved as a parallel approach to Service-Dominant Logic; which is based on the idea of changing a traditional view of products towards systems of products plus services. PSS highlights a change in the offering; which is that customer retribution is on the use of a system rather than acquiring the system. Tukker [51] presents different types of Product-Service Systems: • Product oriented services: where the focus is on product sales and some additional services related to the product, advice and consultancy. • Use oriented services: where the product plays an important role but the business model is developed for a service; this includes product lease, product renting/sharing, and product pooling. • Result oriented services: where there is no predetermined product involved and the agreement is on a result; including activity management and outsourcing, pay-per-service unit and services based on functional results. Based on these categories, we can argue that MTC technologies will be largely offered as product oriented services. At the same time, we consider MTC as an enabler of other product oriented services (related to monitoring) and, more importantly, an enabler of use- and result-oriented services for other industries. We go back to Normann and Ramirez’s [26] argument to suggest that it is no longer possible to define fixed positions for firms based on a set of activities along a value chain; therefore the focus should be on the overall system. This argument is the basis of the value network model presented in the previous section. We recap on this notion to highlight the implications in the MTC research context, which is that even MTC technical experts should be aware of aspects beyond connectivity, in order to channel their effort to challenges that can be solved by technical improvements. As a result, we believe that the study of MTC should never lack a context; and be solely studied from connectivity perspective. The context is then a system of systems, as implied by IoT [52].

Mazhelis et al. [15] present a definition for IoT ecosystem from an ICT standpoint, with focus on the device and connectivity roles and services on top of the connectivity. Their organization is exhaustive, but it can be regarded as an elaboration for the IoT providers’ ecosystem. The next frontier is to go beyond these providers’ ecosystem and focus on the demand side, since experience is showing that solutions based on MTC require a detailed level of understanding of both: the connectivity field and the area on which the service is delivered. Moreover, as suggested by Leminen et al. [53], most of the critical challenges cannot be appreciated at a firm level, but rather on the ecosystem or network level and, more importantly, on the industry boundaries. The IERC [55] presents the same idea by suggesting that the purpose of MTC is to support applications that are not part of the ICT domain. From Harbor Research [56] we can get a more direct statement, they elaborate that there are no significant ecosystems in the area besides early emergent alliances. Moreover, they claim that “business development among technology developers has not kept pace with their techst nology innovation. The tech tools may be 21 century, but the business thinking of the tool “creators” has too th often remained in the 20 ”. They refer to the fact that technology firms should avoid the command-and-control type of relationships that suited the inception of MTC. It is possible to find support for the argument that the slow emergence of solid ecosystems is due to the fact that there are too many technologies and firms creating isolated solutions, resulting in a fragmented market. On the next section, we elaborate on this topic.

3.3. Discussion on Fragmented Market There has been an increasing attention on the debate related to the shared and common solutions in the MTC context as an incentive to reduce investment costs and expand business opportunities [57] [58]. The IERC high†† lights the obstacles of having a fragmented market [59]. Nonetheless, one needs to be cautious with referring to a fragmented market as a challenge; since it is just a condition in the market that opposes to concentrated market—which in turn is associated to monopolistic behaviour and innovation decay. It is perhaps the fragmented offering the factor influencing the rapid expansion and innovation in this sector. Furthermore, IoT and consequently MTC are fragmented by nature, because the end needs cannot be homogenized and systems become so

3.2. IoT as the System of Systems Here the work from Leminen et al. [53] [54] regarding ecosystem business models for IoT is particularly relevant; where they claim that businesses cannot be anymore understood from a single actor perspective and the value creation and exchange requires active involvement from all the relevant actors and needs to be understood across the network of companies. In the case of IoTenabled services, enabling actors—including MTC actors and other communication providers—play a fundamental part; their involvement in the service provisioning is dynamic, therefore, these firms need to understand and develop the business and offerings conjunctively.

††

A market is fragmented when there is no clear leader or dominant company in terms of market shares, i.e., no company is influential enough to move industry in desired direction.

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highly integrative. Werner Mohr, chairman of the 5G Infrastructure Public Private Partnership (5GPPP) explicitly mentioned that 5G will not only be about a new radio access technology, also the network architecture will have a focus for development [63]. Even more, 5G should provide the integration of cross-domain networks. There seems to be an agreement on the premise that 5G should be able to provide a future-proof architecture that could be afterward driven and managed by software in order to address a diverse range of services. Now the question is why we need such a “disruptive network”. All generations of cellular communications up to 4G have been developed based on a set of technical requirements, in order to accommodate better user experience for end-users of cellular telephony. This has been due to the fact that the technology has had a vast potential to be enhanced and the market, yet, has not been saturated. At the same time, starting from 2G, some potential had been seen in this domain that could have helped other industries to transform to a better state; mainly based on data provisioning. Now for the emergence of 5G, recalling our discussions on Teleeconomics, the “why” question at the beginning of this paragraph turns to: Is 5G going to be a Technology Push or a Market Pull? If we look into market demand for 5G and seek for industrial needs, one valid example can be massive MTC. It is believed that many industrial MTC-based demands can be met by legacy technologies combined with improve§§ ments on 4G standards . For instance, one major initiative in this regard is the CIoT. GSMA launched the Low Power Wide Area Network Initiative to accelerate the rollout of complementary cellular networks for MTC. The focus is on “applications that have low data rates, long battery lives and that operate unattended for long peri- ods of time” [64]. The 3GPP presents a technical report that considers both the possibility of evolving the some of the current system and the design of a new access system to meet the requirements for a Cellular IoT system for the lower data rate end of the M2M market [65]. This initiative has the purpose of covering the existing MTC demand and deployments are expected by 2016. Looking into the MTC demands from market, that can lead driving the emergence of 5G, it can be considered that Critical MTC for health, traffic safety, and industrial control will be the drivers. Looking back to our discussions on “MTC and Services”, by focusing more on the importance of Tele-economic research, in recent years

complex that is not possible to serve them with a single solution [53]. The IERC [59] suggests that “focusing on vertical applications risk reinforcing silos and prevents innovation”. Endeavours towards horizontalization are coming from the telecom sector, in order to standardize solutions and scale their offer. In this sense, it is important to recognize the achievements on the standardization and global alliances in this respect [60] [61]. In short, enabling firms should have a standardized vision while innovation should be provided on specific aspects since precisely the vertical applications will be the revenue generators. Cur- rent market development corresponds to this argument; that meaningful solutions for industries and societies are achieved vertically, by fully integrating the non-ICT actors in the value design and development. It is important to understand that even if standards are established and dominant designs are adopted, there could still be negative fragmentation in the offers. As shown in [28], having the same standard technology will not prevent an adverse fragmented market on the service level. This service level fragmentation can negatively affect the experience on the customer side, limiting the adoption of such services. Therefore, it is convenient to have the service and the user experience as the starting point for the further development. Finally, a deviation in the notion of benefits of scales is taking place in several industries. While standards serve the purpose of providing tools to interconnect efficiently, “problems” cannot be solved from a topdown approach; solutions come from local contexts and this notion should be embraced, rather than being treated as a challenge. This can also be seen as an operator trend, with a change in focus from global to local as a strategy to achieve better synergies while keeping a ‡‡ trade-off with scales . Therefore, our final argument is that the main barrier towards IoT is not on the lack of reference architectures or technology fragmentation; we argue that the real barrier is that the value is not clear in many solutions. In the next section, we discuss the emerging changes shaping the development of 5G, considering the growing interest in MTC.

4. Towards 5G Andrews et al. [62] argue that 5G is not going to be an advanced version of 4G, but instead a paradigm shift including many high technical requirements that are

§§

As presented by Sara Mazur, Vice President and Head of Ericsson Research, Ericsson AB, during Keynote; “Technology research for industries and society in transformation” at the Ericsson Research Open Day, September 2015.

‡‡

As presented by Bengt Nordström, CEO at Northstream AB, during the seminar Key telecom vendor trends, Key Operator trends and Thoughts about the IoT market at Wireless@KTH on October 2015.

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Tele-Economics in MTC: what numbers would not show there has been a transformation towards a service enablement mind-set by some actors [66]. This then makes 5G the flipping point from a technology push to market pull. As a result, we believe that Tele-economic research on MTC is “the” way to address efforts towards 5G. Relating to the aforementioned change from technology push to market pull, major stakeholders of the telecom industry value network are following co-creation of value under the PSS concept in 5G. These are the legacy providers of solutions, equipment and services. For instance, Ericsson introduces the idea of logical network slices to enable operators to provide networks that meet the requirements of the wide range of cases, with a combination of SDN and NFV [67]. On the other hand, Nokia has presented the notion of a service enablement domain to allow operator the possibility to grant secure access to thirds parties to develop vertical services based on a SDK [68]. These two clear directives toward service enablement are also supported on ZTE´s vision that the development focus for 5G should not be about network capacity but rather on the user experience [69]. From the other side, the market demand for Critical MTC in 5G would cause a deeper integration of ICT in industrial processes, products and services, which will strengthen competitiveness of industries. This argument can be validated by Arcas’ discussion [70], which believes M2M [MTC] adoption has been driven by value creation and not by technology availability. We argue that we will see a more reciprocate relationship in the evolution of requirements and supply of new solutions. Further on, we rely on Simon Sounders’ considerations for 5G [71], mentioning that it is important to look carefully into the users for 5G standards and what implications they might bring. We reached a shifting point and in 5G will explicitly target specific needs on vertical industries. “Rather than rushing out the next generation of cellular technology to meet arbitrary deadlines, time needs to be spent now thinking about how 5G can serve the wider societal and industrial needs” [71] [72]. Our concluding remark on this section is that industrial customers do not actually want 5G systems; these customers just want to solve problems on their industries.

activities. As a result, we conclude that the study of MTC should never lack a context, which is largely related to the industry or sets of industries where the solutions will be of use. In addition, we emphasize the role that MTC has as driving force for the product-to-service transition in the economy. Further on, we show how the service enablement mind-set in the telecommunication industry in having a profound impact in the development course of 5G standard, which has been largely focusing on addressing specific needs for vertical industries. Acknowledgements This work has been partially funded by Wireless@KTH and the EIT Digital innovation project EXAM.

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Chapter 11

Repositioning in Value Chain for Smart City Ecosystems -a Viable Strategy for Historical Telecom Actors Amirhossein Ghanbari, Óscar Álvarez, Thomas Casey, Jan Markendahl In the American Regional International Telecommunication Society conference, Los Angeles, USA, October 2015.

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Repositioning in Value Chain for Smart City Ecosystems - a Viable Strategy for Historical Telecom Actors ú , Thomas Casey† , Jan Markendahlú ´ ´ Amirhossein Ghanbariú , Oscar Alvarez ú

KTH Royal Institute of Technology, Stockholm, Sweden †

{amigha, oaa, janmar}@kth.se

VTT Technical Research Center of Finland, Finland [email protected]

Abstract In a historical business model, Mobile Network operators (MNO) design their own network, own their infrastructure, operate the network and offer services on top of it; a voice-revenue dependent business. Now with the data provisioning, since the revenues associated with data do not comply with the pattern of increasing data usage in mobile networks, MNOs need new revenue streams. As a result, MNOs have started changing their business models by offering services besides their usual competences. This complicated approach has then forced them to think of possible cooperation patterns in order to benefit from horizontal collaboration with others, instead of being vertically integrated. On the Other hand, Telecom Equipment Vendors (TEV) used to design their business models in a vertical manner as well. TEVs would build and manufacture equipment and sell them to their customers in a Business-to-Business (B2B) fashion while in some cases operate the networks on behalf of their customers. Looking for new markets and revenue streams, the future Smart Cities comprise a good opportunity for MNOs and TEVs. This opportunity then requires a new mindset among these actors. In the new mindset, these actors should accept to reposition themselves in the new value chain. This means that, in order to play a role that can not be overlooked, MNOs and TEVs should perform rather different blocks of the Smart City value chain. This paper intends to provide an analysis of how the traditional telecom actors (MNOs and TEVs) have changed their business strategy and repositioned in the context of the Smart City service provision. In order to do that, we will introduce the traditional telecom actors and the existing value chain, later on, smart city concept and use cases will be introduced, finalizing with an analysis of how the future smart city value chain and the repositioning of these actors. Index Terms Business Model, , Horizontalization, Repositioning, Value Chain, Smart City, Telecom Actor.

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I. Introduction The concept of Smart City, which is the use of Information and Communication Technology (ICT) to sense, analyze and integrate the key information of core systems in running cities, is often considered as a subcategory of Sustainable Smart City (SSC). A SSC is defined as an innovative city that uses ICT and other means to improve quality of life, efficiency of urban operation and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social and environmental aspects [1]. In this concept, Integrated Infrastructures of co-exiting involved industries play a leading role since sustainability is highly dependent on collaboration. Furthermore, existence of multiple infrastructures in the same industry is highly inefficient and would lead to lack of sustainability. ICT as the major enabler of Smart Cities is in the forefront of infrastructure integration. On one hand, Telecommunication infrastructures play a vital role in enhancing the connectivity and sustainability of the cities and on the other hand Machine to Machine (M2M) communications play an important role within ICT for enabling SSCs. M2M communications for Smart Cities refers to the exchange of information between autonomous devices in control and monitoring applications without human intervention [2]. The decline in communication fees, altogether with the massive adoption of real-time access of information is expanding the consideration of new services and applications and solutions based on this type of communication. Different actors are trying to position themselves in the M2M market by providing different set of solutions, including information management, network deployment, systems integration and so on [3]. Moreover, the pressing situation faced by telecommunication operators, triggered by the saturation of their traditional revenue streams (voice and data) in developed countries [2] is also resulting in an increasing interest in the interconnection of smart devices and sensors by operators. On the other hand there are new actors that are also seeking for strong positions in the M2M ecosystem, targeting different roles. All of these leads to co-existence of many actors whom are competing in the same market while they need to cooperate in order to benefit fully from opportunities. For instance, one evident form of cooperation is sharing resources such as infrastructures. In this context, this paper aims to provide useful insights in the repositioning of the traditional telecom actors in the new value network redefined for city ecosystems. The final goal of this research is understand and describe how new services and applications are changing the complete industry, forcing the historical actors to adapt and compete in new fields. In order to clarify the topic of the paper, the following research question is introduced: Where is the place for the MNOs and TEVs in the Smart City ecosystem? The paper is structured as follows: Section I introduces the context and the aim of the paper, Section II describes the methodology followed, Section III describes which are the considered historical actors in the telecom industry, Section IV describes the traditional value chain for telecom actors, Section V introduces the concept of smart cities and its defining building blocks, Section VI introduces a number of use cases in order to better understand the diversity of services and how the actors collaborate in a Smart City context,

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Section VII concludes by describing the repositioning of the traditional telecom actors in the new context. II. Methodology The methodology includes a two-stage approach. The first stage provides information on existing practices for MNOs and TEVs in the existing value chains. The second stage provides an analysis with the objective to identify recurring patterns across the different cases. The analysis is focused on producing insights into how actors cooperate and how they distribute their roles and also to identify and understand the drivers and obstacles for introduction of repositioning and cooperation strategies. For analyzing data, Analytic Induction and Grounded Theory methods will be used [4] [5]. These two are iterative methods that alternate between collections and analyses. The iterations continue until no cases dismiss the hypothesis or theory. Analytic induction stops when the hypothesis and grounded theory ends with a validated theory. Value Analysis and Empirical Data Analysis will be performed. The value analysis framework consists of conducting content analysis of collected data and studied literature in order to understand the context of the actors’ decisions, intention and opinion. On the other hand, Empirical data Analysis framework will be mainly used in order to perceive the current situation in the market and major drawback of implementing a coopetetive system. III. Traditional telecom actors MNOs are the typical carriers that control and operate mobile networks as well as managing customer relations, where customers refer to end users with User Equipment. Traditionally MNOs used to implement a complete vertical solution handling all different parts of the network as well as the CRM. As it was illustrated in Figure 1, a shift from historical value chains is happening in the telecom ecosystem towards new business models. This shift has made operators think about their possible role in the M2M communications and connectivity. In Figure 1, the hierarchy shift in the telecom/internet sector is shows. It can be observed how MNOs are losing its control and influence in front of OTT services providers.

Fig. 1: MNOs dominance hierarchy and the coming shift TEVs in the context of Telecommunication imply those manufacturers of the telecom equipment that provision the technical procurement for the operators. Again, according to the shift in the value chain, the TEVs have recently participated in different roles that historically have been assigned or taken care of by

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others, mainly MNOs. for instance, it is now quite an accepted concept that TEVs operate and maintain networks on behalf of MNOs, helping them focusing on their core business that is taking care of customers. When it comes to M2M ecosystem, some major TEVs have their vertical M2M solutions that in some cases are considered as the most complete solutions. This can only be done upon diverse capabilities of big NVs globally due to interaction with MNOs as well as being expert as operators of mobile networks. IV. Traditional value chain Here the traditional value chain in the telecom sector is described. A historical value chain in Mobile Telephony provisioning corresponds to two major activity blocks. This has made it clear for TEVs and MNOs where to participate in this value chain; TEVs taking over “provisioning connectivity” and MNOs taking over “End User management” and “Service Provisioning”. The positioning strategy for these actors then have been somehow clear and the value chain made it easy for them to collaborate with each other, while competing in each block with similar entities (i.e. other MNOs and TEVs).

Fig. 2: Simple value chain of Mobile Telephony (top) and Historical Actors’ positions (bottom) MNOs historically obtained revenue by offering wireless connectivity to private users; a Business to Customer (B2C) setup. TEVs on the other side played the role of suppliers for the MNOs. This connectivity in the early days meant cellular telephony, which has evolved during years and now includes Calling, SMS/MMS, and Mobile Broadband. In addition to obtaining revenue by offering retail services under its own brand, a MNO might have also sold access to network services at wholesale rates to Mobile Virtual Network Operators (MVNO) in a Business to Business (B2B ) setup. Figure 3 illustrates the major business relations for MNOs and TEVs in the Mobile Telephony case. A Managed Service Partner (MSP) is typically an outsourcee for MNO’s network operations (e.g. outsourced NOC). Outsourcees have been either third parties or in most cases the TEVs that operate the networks for MNOs.

Fig. 3: Two illustrations of Historical Value Network of Mobile Telephony

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Besides minor incentives, three main reasons have driven MNOs to consider changing their position in the Value Network and start to collaborate with their direct competitors in the market: a) Cost reduction, b) Lack of spectrum, and c) Coverage Expansion. In the most common setting, two or more MNOs form a joint venture (figure 4-left) that owns the access network (or parts of it) but the Customer Relation Management (CRM) is still being handled by each operator. When it comes to policy, the telecom National Regulatory Authorities (NRA) has long been the regulator body in this industry. The main role of the NRA is to enable “proper” access to spectrum for different MNOs while supervising their utilization of this invaluable resource. Merger (figure 4-right), as a strategy for gaining more market share or a viable exit strategy has also become a common practice among MNOs. This setting highlights the role of the “competition” authorities since the case of merger can directly give or take Significant Market Power (SMP) to a specific MNO.

Fig. 4: Network Sharing and Merger

V. Smart Cities There is no common and widely accepted definition for Smart City, just slightly different definitions of this concept depending on the implementations. In this paper we will consider the definition from [3], a ” Smart City is one that is able to link physical capital with social one, and to develop better services and infrastructures. It is able to bring together technology, information, and political vision, into a coherent program of urban and service improvements.” To start, we need to define which are the main aspects that the Smart City (SC) concept covers. In this sense SC is commonly related to five main building blocks: • • • • •

Economic, Social & Privacy Implications Developing E-Government Health, Inclusion and Assisted Living Intelligent Transportation Systems Smart Grids, Energy Efficiency, and Environment

A. Economic, Social & Privacy Implications It is a mistake to think that making smarter cities requires just more investment in development of technical IT (Information Technologies) solutions – technical development should be aligned with the social

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and economic goals of the society. The most important issue confounding efforts to make cities smarter is not the development of appropriate technologies per se, but to tackle the difficulties in changing organizations and existing ways of working to use these new technologies to deliver smarter cities. Therefore, the provision of services should be focus on improving the current performance of the urban services with the ultimate goal of improving efficiency, efficacy and life quality for the final users-citizens. B. Developing e-government The existence of Internet and electronic devices provides the opportunity to implement e-government systems, where citizens would have a voice in every decision make on the city. The implementation of egovernment systems is, at the same time, a big opportunity and a big challenge as it will require open minded administrations, committed citizens and technical maturity. Another aspect to consider for development of e-government is the integration of data and IT systems into the public policy and administrative procedures [6]. In this context, a new evolution regarding the public administration and ICT adoption is characterized by incorporate more opening and collaboration, allowing the creation of open innovation processes in connection to the public procurement. Therefore this enables a change from public-private partnerships to public-privatepeople partnerships, which implies higher level of participation and democracy to the citizens. This concept is included in the vision of Smart City, where Open Government and governance play a primary role that requires public policies and strategies oriented to achieve social sustainability in benefit of all the society [7]. C. Health and Assisted Living One of the main concern of developed countries is the fast aging effect on the society, where an increasing percentage of the population is elderly. This situation brings challenges in terms of provision of welfare services and benefits, where health-care is the cornerstone. The concept of Smart City considers ICT-based solutions for home-care, elderly care, chronic diseases and tele-care services, with potential benefits in terms of efficiency for the public health sector [7]. Many existing and potential technologies under development for the maintenance and/or supervision of health and well-being offer a great promise, ranging from health monitoring services and falls detection to “lifestyle monitoring” (detecting changes in behavior patterns). Within this realm, research in ICT platforms for elderly and people with chronic diseases test ideas of generic health monitoring platforms, addressing people with chronic conditions, and assistive mobile devices, among others. Smart Cities need to incorporate these aspects into their overall structure and roadmap [8]. D. Intelligent Transportation Systems As an in industry that has been around for years, Public Transportation has gone through considerable changes with the aid of ICT. World population is expected to grow from 7.0 billion in 2011 to 9.3 billion

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in 2050 according to an UN prediction [9]. At the same time, the urban population is projected to grow by 75 per cent in the same time period, from 3.6 billion in 2011 to 6.3 billion in 2050. Thus the urban environments will not face only a direct increase in population but also a massive migration coming from the rural areas. A key area that cities will have to address is the mobility issue. More specifically, due to population increase, congestion issues in urban environments might become critical. This means that the current transport systems have to be extended in order to face the increased population. In order to be efficient, the transport systems have to be connected, and here is where the multimodal transportation systems come up front. This concept implies a chain of trips combining different means of transport (personal car, buses, trains, metros, etc.) allowing the user different combination of modes to go from one place to another. In this way, the strengths of different transport modes are combined in order to offer a more flexible and reliable experience to the end users [10]. Users nowadays are looking for the most efficient way for traveling from A to B. By combining different means of transport with their associated waiting and travel times, multimodal transportation succeeds to optimize the current infrastructure and lower the changing time. This increases the efficiency and overall customer experience making it more convenient to use [11] [12]. E. Smart Grids, Energy Efficiency, and Environment Smart Energy or Smart Grid is one the more important aspects of the Smart City concept, enabling responsible management and operation of energy networks in cities. The integration of communication infrastructure, mathematical modeling techniques and simulation techniques can be a powerful tool in this context. The concept of Smart Grid also includes the idea of “prosumers”, which it the idea of integrating decentralized energy generation in the nowadays centralized energy grid, enabling householders to produce its own energy and sell and buy from the energy grid depending on its consumption. This also holds for the potential storage capacity for both electrical and thermal energy within energy networks, which can be achieved by intelligent demand side management. [13] A major requirement in Smart Cities is to leverage energy consumption between the different producers and consumers, which directly translates into reducing the pollution generated by today’s cities and the emerging mega cities [14]. In this concept, efficiency improvement in water and waste management is included. Such important resources need to be optimize and organize in the most efficient way by using ICT technologies. F. ICT Integration/Horizontalization In the business domain these new services related to the Smart City concept require cooperation and collaboration from many different actors; including public institutions, telecom operators, utility providers, OTT (Overt-The-top) providers or transport companies. The strength of the Smart City concept, gathering the value of data and ICT integration from different sectors, remains also its biggest challenge. The authors consider that the main challenge for Smart City services development is the definition of business models suitable for these services, where all the actors involved would benefit and collaborate from the provision of

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the services. Another relevant issue when talking about Smart Cities is the communication infrastructure needed; we still need answers to questions like: Which technology to use? Who will be the provider of the network? Will all services run over the same network? Telecom researches have been discussing on the idea of horizontalization of Smart City services, which means the idea of having one common network (cellular or wired) and/or platform for all services related [15] [16].

Fig. 5: ICT Horizontal collaboration/multi-actor market [15]

G. Smart City M2M resources When it comes to the role of ICT in Smart City, a set of resources enable the Telecom actors to participate and perform different sets of activities. The importance of these resources lie in the fact that possession of any of these resources enables an actor to perform a specific activity. By a resource it is meant anything which could be thought of as a strength or weakness of a given firm. More formally, a firm’s resources at a given time could be defined as those (tangible and intangible) assets which are tied semi permanently to the firm [17]. Examples of resources are: brand names, in-house knowledge of technology, employment of skilled personnel, trade contacts, machinery, efficient procedures, capital, etc. [18]. Defined pedagogically, Grant [19] categorizes Resources into six major categories; Financial, physical, human, technological, organizational and reputation. • • •

MTC Infrastructure M2M Platform End-user

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• • •

M2M Data Capital Knowledge/competence

1) MTC Infrastructure: When providing communication services, the need of communications networks appears naturally. Within communication networks two different types can be identified: Core network and Cellular access network. The core network is the central part of the communications network, facilitating the connection between different sub-networks. The Cellular access network (also defined as radio access network) is the interface between the end-user and the core network, basically using wireless technology connecting to a base station close to the end-user. The communications infrastructure is usually owned by a MNO, which has done long term investments in its deployment with the final goal of providing communication services to individuals, companies and organizations. 2) M2M Platform: One major barrier that the development of smart cities is facing is the existence of vertically integrated industries developing its own smart city solutions. [20] [21] In order to tackle this issue the development of a common platform integrating services from different industries is needed. The platform acts as a common ground for the development of services and applications on top of it, providing an open environment for collaboration between industries and supporting innovation in the context of smart sustainable cities. 3) M2M Data: One very important resource when introducing smart cities and M2M services is data, data originated for the end-users on the city. Data can be defined as all the information obtained from the usage of a number of services in the city environment; communication/Internet services, transportation services, energy consumption, car-sharing, parking or logistics. The added value in smart sustainable city comes from the obtaining a big amount and data, process the data and extract useful information for the decision making in the city. The data is generated from a number of different sources and stakeholders, going from the MNOs and service providers to the city governance. This data needs to be shared in order to apply analytics and the information obtained needs to be open and usable, first to the decision makers and later on to the other partners involved in the provision of services. Therefore data is considered as one important resource to be shared in this context, being of key importance in the provision of smart cities services. 4) End User: The final goal of these services is to provide useful information and services to the end-user, which will be able to make better decisions on how to interact with the city. In the provision of these services, a number of actors are involved and it is not feasible that the end-user has relations with all of them. The usual relations with the user are with either the service provider or the MNO, being both of them in the front-end of the business activity. In this sense, the different stakeholders are sharing this resource event though not all of them have direct relation with it. Why is End User/Customer an important asset? On economic terms, what is important for a firm is higher profit. Profit is a financial benefit that is realized when, in a business activity, gained-revenue is more than all expenses (including taxes, costs) [22]. The

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source of the revenue gained by the firm is then the price the customer pays. Revenuef orP roducer = P ricepaidbyCustomer ú numberof Customers For a customer, value is defined as the ratio between the benefits they receive and the price they pay. V aluef orCustomer = Benef it/P rice Considering that the Value for a firm (producer) is reflected as financial profit; value is the difference between the revenues they receive and the costs they incur. V aluef orP roducer = Revenue ≠ Expenses So it means that more profit for the producer can be gained by: • • •

Creating more benefit for customers Increasing the number of customers Lowering expenses

It could be concluded that customers are the economic resource which are subject to be cultivated by the producer [23] VI. Smart City use cases In this section a number of Smart City use cases will be introduced, with the ultimate goal of obtaining insights on how the value networks and value chains are created in this new context. For this purpose, three sectors where a change from a vertically integrated market to a more horizontal/multi-actor market is already happening or is predicted to happen. This idea of horizontal collaboration is illustrated in figure 2. The three selected industrial sectors are: Mobility, Built Environment and Energy and Clean technologies. A. Mobility For the mobility sector we examine the current state and the evolution towards multi-city, multi-vendor real-time information solutions. In addition to that, we consider the case of Mobility-as-a-Service (MaaS), a multi-actor environment that provides seamless door-to-door services for end users by combining several modes of transportation. In the traffic domain there has been a movement towards collection of various types of traffic related data and utilization of this information in decision-making. The latest trend is provision of traffic data through standard interfaces in order to enable production of diverse types of services. Currently there are parallel efforts taking place to promote creation of real time traffic information to improve situation awareness of transport users and traffic managers. The current vision is to create a distributed situation awareness capability to provide diverse inputs to transport users. This capability should emerge over time through development of various interlinked services utilizing diverse sources of data, exploiting different technologies, and provided to a variety of transport

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users and operators, both public and private. This will require collaboration and interoperability to enable transmission of data between various players. Taking as a use case the development of mobility services in Finland, we can observe that the cities of Tampere and Helsinki have started a public procurement where research and development services are purchased from multiple vendors. The services to be developed can relate to various types of traffic information such as road transport, pedestrians and cycling, weather and air quality, selection of traffic mode, traffic management, or forecasting. In this tendering the pre-commercial procurement (PCP) approach is used where multiple firms are selected to undertake simultaneous product development in two consecutive stages. In these initiatives interoperability is an explicitly stated goal. It is promoted by provision of open public data in standard formats. It is also pushed forward by the vision of a marketplace of data, tools and applications which are produced by a variety of firms and public sector actors. Availability of traffic data standards (e.g. Datex II, SIRI) is an enabling factor for development of interoperable services which also have potential to scale up to international markets. However, at this stage of rather early development of real-time traffic information services, alignment of national and regional developments has only been started. 1) Mobility-as-a-Service: One flagship example of smart city development in the mobility sector is the evolution towards the so called Mobility-as-a-Service concept (MaaS). The basic idea of MaaS is to provide a seamless door-to-door service for end-users which combines several modes of transportation (e.g. local and long distance busses, trams, taxis, demand responsive public transportation and shared private vehicles) and serve it as one simple package for the end-user. In principle this would mean that the end-user would for example not need to have separate accounts and tools for each mode of transportation for planning their trips and paying. The evolution towards such a new paradigm is driven by many trends such as urbanization and by the fact that young people are not acquiring drivers licenses as often as before, i.e. do not necessarily want to own a vehicle but would instead like to have access to a better supply of transport services. The underlying driver is also the accelerating development and application of ICT technologies in the field of mobility. Vehicles are increasingly being instrumented with positioning systems and mobile broadband connectivity and linked to cloud services. Furthermore, end-users are more and more equipped with smart phones and applications that provide access to different transport modes. Over the years there have been major advances in the utilization of ICT by the different transportation providers. Journey planners have become commonly used tools for end-users to organize their trips. Vehicles are also increasingly instrumented with locations sensors. For example in Tampere all busses and in Helsinki all trams and many of the busses are equipped with a location tracker which in principle makes it possible for end-users to dynamically alter their routes. Demand responsive public transportation concepts have also been developed where the leading pilot at the moment is HRT’s Kutsuplus. However, if one looks at the current systems deployed, it can be stated that the related ICT solutions, that are the building blocks for MaaS, are heavily fragmented and tailored for different transport modes and

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providers. Vertically integrated solutions with limited interoperability are built for local public transportation, long distance public transportation, taxis, ride and vehicle sharing and private vehicles. Most are also tailored to specific regions and not interoperable across cities. The potential market for MaaS consists of a large group of stakeholders ranging from actors in the public sector responsible for legislation, regulation and organizing public services (e.g. public transportation) to actors in the private sector such as transportation operators (e.g. bus and taxi companies). A wide group of ICT solution providers also exists ranging from large IT companies (such as Tieto, CGI and Accenture) who provide large ITsystems to transport operators (e.g. related to ticketing) to SMEs providing systems to Taxi Switching centers (e.g. Semel and Mobisoft) and to individual software developers developing e.g. mobile journey planner applications. In addition to this private vehicles are also often instrumented with on-board units that enable real-time services (e.g. related to remote diagnostics, driver coaching, driving diaries and emergency call (eCall)). Furthermore many internet based ride sharing communities exist (e.g. in Facebook) and dedicated applications are also emerging (e.g. Ridefy). Therefore, although the sector is rather fragmented, the end-users already now have quite many tools to optimize their transport services. In order for MaaS to reach its full potential these ICT solutions need to evolve towards more modularity and interoperability across regions and transport modes. Tekes for example defines three types of information to which open access is required from existing transport service providers: • • •

Timetables, Real-time location information, and Payment systems.

2) Connected Vehicle services: In addition to the previously described MaaS, there is another type of services which can be included in the category of Connected Vehicle Services. Connected Vehicle Services is commonly defined as the set of services based on ICT technologies and provided during the driving experience. This category includes a number of services ranging from: •

Remote diagnostics: Service that provides access to the OEMs (Original Equipment Manufacturer) and allows them to perform proactive remote diagnosis of the vehicle functionalities, schedule service booking, order spare parts in advance and software updates.

•

Emergency call – eCall: This service provides fast and automatic communication with emergency services when an accident happens. This communication can be done through SMS or telephonic call.

•

Mediaroom-Infotainment: In-car media and entertainment services such as IP TV, video games or streaming music or movies. Companies like AT&T and Ericsson have already developed platforms in order to provide this kind of services.

•

Insurance billing: Vehicle connectivity can be used by insurance companies to charge more or less depending on how the drivers use the car. Concepts like “Pay-as-you-drive” or “Pay-how-you-drive” use connectivity to detect the driving style and use this information in the billing process. This kind of

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systems can detect driving style, usage time, distance travelled or average speed. In the context Connected Vehicles services provision, a number of activities have been identified. The main activities identified are: Connectivity provision, SIM card provision, Platform management and provision and user management and relationship. Considering these main activities, we can observe different setups regarding collaboration between actors providing these services. In order to illustrate these different setups we will briefly describe two already existing services: Tesla and Volvo connected cars.

Fig. 6: Tesla VS. Volvo Volvo Connected Car. Volvo is currently offering a service named Volvo Sensus connect, which basically is a commercial offering embedded in Volvo vehicles that allows the user to obtain services related to and enabled by ICT. The setup for the Volvo Sensus connect has been aiming to enhance collaboration between a number of actors, allowing each actor to focus on its field of expertise. The activities distribution has been as follows: MNO taking care of connectivity and SIM card provision, TEV handling platform development and management and Volvo providing end-user management. Tesla. Being one of the most innovative car manufacturers in the world and aiming to disrupt how the car industry works, Tesla also has a slightly different approach regarding Connected Vehicle services. Tesla Connected services are taking that concept one step forward, fostering ideas like software updates enabling autonomous driving in your car. In addition to be a cutting-edge car manufacturer,Tesla has selected a different approach when developing Connected Vehicle services. Tesla’s strategy has been integrating and controlling all possible activities. Therefore Tesla concentrates activities on end-user management and platform development, leaving connectivity provision and SIM card provision in hands of of the MNOs. In this activities stack, it is important to highlight the importance of differentiate SIM card and Connectivity provision. As we are talking about vehicles, roaming plays an important role. Roaming should be implemented between different countries, involving different MNOs with corresponding roaming agreements. The roaming process should be seamless for the end user; hence the actor in charge of the end user

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Fig. 7: Activities stack options for Connected Vehicle services a) Tesla setup b) Generic activities stack c) Volvo stack

management should include roaming aspects in its agreements with MNOs. An example that can be useful is the Amazon Kindle service, where the user can buy books from its device anywhere in the world using cellular connectivity. Companies like Tesla or Volvo should establish similar agreements with connectivity providers. In this sense, SIM card would be provided by one specific MNO while connectivity would be provided by many MNOs. In addition to this approach, we can also envision how the implementation of SIM cards can potentially change in the future. New implementations like soft-SIM cards will have an impact and make a change on how companies or individuals access connectivity services. B. Digital Urban Environment 1) Waste management: Smart Waste is part of the smart city concept. Focusing on municipal solid waste, Navigant Research defines Smart Waste technology as the integration of advanced technologies into a strategic solution that enhances sustainability, resource efficiency, and economic benefits. The use of these technologies results in more integrated waste management offerings that move beyond the traditional use of labor, diesel trucks, and open pits to discard waste. As an instance, for the specific case of Finland, Waste management is getting smarter as new technology is implemented in different areas of the country. New incineration or composting plants are directing waste streams away from landfill to higher levels or smarter waste management. Here we will, though, focus on applications of Smart Waste making use of IoT (Internet-of-Things) technology. Early experiments with IoT type solutions in Finnish waste management industry involve a scale for measuring the mass of waste in the garbage truck before emptying the load at the waste station. Today a few smaller companies, mainly start-ups, are providing Smart Waste solution for container fill level monitoring

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and waste sorting. Enevo is at the moment receiving a lot of publicity, but also companies like MariMatic Ltd and ZenRobotics Ltd have presented innovative solutions for waste management. Overall, the number of companies involved in the Smart Waste area in Finland is limited and since the use of monitoring technology is only at an early stage little need for integration or interoperability has yet been needed. The waste management system is seeing rapid changes. The change from landfills to incineration is shaping the structure of the system from municipal into larger areal networks. This will have an effect on how waste management is organized, what technology is used and how business is done. Today there is, however, evidence of new IoT based solutions being developed and implemented is limited. Future needs to increase recycling of products, parts and materials can become the incentive to implement more Smart Waste solutions. Recent discussion on circular economy stresses the fact that raw materials are becoming scarce and that all material need to be re-used and recycled in several iterations. This will probably also create a need for close monitoring of material in the society and industry, thus increasing the need for information from a wide spread of information sources. C. Bigbelly Solar Inc. BigBelly Solar, Inc. provides solutions for the management of waste and recycling. It offers solar intelligent waste collection systems to manage the process of collecting solid waste, as well as solar compactors, and companion recycling bins and kiosks; CLEAN, a wireless network monitoring and management software that provides real-time and historical information to managers or workers to plan waste collection routes and pickups; and Connect™, a turnkey smart waste and recycling system that ensures customer engagement and satisfaction. It serves municipalities, cities and towns, college and university campuses, parklands and beaches, government and military installations, and institutional customers [24].

Fig. 8: The Complete Bigbelly Solution [25] An elaboration on how bigbelly works as a system in the USA is as follows:

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• •

Bigbelly solar compactors are upgraded with wireless hardware. CLEAN sends data through standard SMS (text messaging) format to our online server (requires adequate cellular phone signal, currently provided by AT&T).

• •

See real-time Bigbelly operational data right at your desk. Monitor collection activity to eliminate unnecessary pickups and free up workers from on-street status checks.

Fig. 9: Bigbelly Solar’s Waste Management vs.Connectivity Provision In accordance with the concept of Digital Urban Environment, Bigbelly also offers cellular connectivity. The company uses its trash bins (consider them urban furniture) as a site for hosting small cellular base stations as well as WiFi access points. The business model then includes offering operators connectivity (cellular), capacity (mobile broadband), and/or carrier WiFi (figure 9 - Right). The idea of utilizing urban furniture for applications beside their prime application is an appealing mindset Smart Cities. VII. Conclusion According to case studies illustrated in figure 6, figure 7, and figure 9, the Vlaue Chain for the Smart CIty while offering a M2M solution is somehow different from Mobile Telephony (figure 2). A simplified value chain for Smart Cities is then illustrated in figure 10 (Top). According to the cases studied earlier, we showed that there are other actors who might be even more competent in provisioning any of the blocks besides MNOs and TEVs. For instance, a specialized M2M cellular network operator (MTC network Operator) can be considered a better option to provide “Connectivity”. Many Service providers have also introduced services for the far right block (i.e. end user management); a previously dominant position for MNOs. On the other hand, TEVs and MNOs have shown interest in all four illustrated blocks. This is mainly because they want to get a bigger share of the revenue from this new business. This is based on the assumption that they can acquire the competences needed to do so. Since specialized actors in each block can perform comparatively better that TEVs and MNOs in some blocks, in order to stay in the game as an actor who cannot be overlooked, they need to reposition themselves in the value chain. One example of a possible repositioning strategy is illustrated in 10 (Bottom). This figure shows a case where TEVs and MNOs collaborate differently compared

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to previous example. In this case, the MNO utilizes the relationship with end-users (i.e. its subscribers), while a service provider offers an OTT service to them (e.g. remote patient monitoring). The TEV offers a M2M platform for this service and the M2M network operator provisions connectivity. Eventually, the same Service Provider offers and manages the M2M enabled devices (patient monitoring devices).

Fig. 10: Smart City value chain (Top) and the repositioned Historical Actors in Smart City value network (Bottom) Eventually, it could be concluded that different actors are capable of and willing to perform multitude of activities based on their Business Models. Keeping in mind the competence and the resources these actors can acquire and/or have, they will be able to cover different blocks of the value chain in Smart Cities. This would then results to two prime positions form MNOs and TEVs (figure 10 - Bottom). In case these entities can acquire more resources in this matter (as mentioned in Smart City M2M resources), they they will be capable of performing other tasks in the value chain. References [1] Focus Group on Smart Sustainable Cities, “Smart sustainable cities: An analysis of definitions,” ITU-T, Tech. Rep. [2] G. Wu, S. Talwar, K. Johnsson, and N. Himayat, “M2m: From mobile to embedded internet,” Communications Magazine, pp. 36–43, 2011. [3] A. Laya, V. Bratu, and J. Markendahl, “Who is investing in machine-to-machine communications?”

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International Telecommunication Society Conference (ITS Europe), 2013. [4] H. Hakansson and I. Snehota, Developing Relationships in Business Networks.

Cengage Learning, 1995. [Online].

Available: http://books.google.se/books?id=Y0FBAAAACAAJ [5] A. H˚ akansson, “Portal of research methods and methodologies for research projects and degree projects,” in Proceedings of the International Conference on Frontiers in Education : Computer Science and Computer Engineering FECS’13. CSREA Press U.S.A, 2013, pp. 67–73, qC 20131210. [6] A. Tat-Kei Ho, “Reinventing local governments and the e-government initiative,” Public Administration Review, vol. 62, p. 434–444, 2002. [7] J. Markendahl and A. Laya, “Transformation of home care services, related working processes and business models due to introduction of mobile technology.” IMP Conference Bourdeaux, 2014. [8] S. Brownsell, D. Bradley, R. Bragg, P. Catlin, and J. Carlier, “Do users want telecare and can it be cost-effective,” in [Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint, vol. 2, Oct 1999, pp. 714 vol.2–. [9] United Nations, “World urbanization prospects: The 2011 revision. new york: United nations department of economic and social affairs/population division.” UN Proceedings, 2012. [10] A. Micheli, “Impact of iot enabled service solutions in the downstream automotive supply chain.” KTH Royal Institute of Technology. Master Thesis report, 2014.

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[11] K. Mesaikos, “Business models for connected vehicle cloud,” KTH Royal Institute of Technology. Master Thesis report, 2014. [12] European Commision, “Transport projects: Closer. retrieved from research and innovation,” 2014. [13] US Department of Energy, “A vision for the smart grid,” White paper US Department of Energy, 2009. [14] O. Alvarez, “Business transformation based on ict: Smart grid.” KTH Royal Institute of Technology. Master Thesis report, 2014. [15] J. Markendahl and A. Laya, “Business challenges for internet of things: Findings from e-home care, smart access control, smart cities and homes,” White paper US Department of Energy, 2009. [16] N. Walravens and P. Ballon, “Platform business models for smart cities: from control and value to governance and public value,” Communications Magazine, IEEE, vol. 51, no. 6, pp. 72–79, June 2013. [17] R. E. Caves, “Industrial organization, corporate strategy and structure,” Journal of Economic Literature, vol. 18, no. 1, pp. 64–92, 1980. [18] B. Wernerfelt, “A resource-based view of the firm,” Strategic Management Journal, vol. 5, no. 2, pp. 171–180, 1984. [19] R. M. Grant, “The resource-based theory of competitive advantage: implications for strategy formulation,” in M. H, 1991, pp. 3–23. [20] A. Laya and J. Markendahl, “The m2m promise, what could make it happen?” World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2013 IEEE 14th International Symposium and Workshops, 2013. [21] E.-J. Kim and S. Youm, “Machine-to-machine platform architecture for horizontal service integration,” EURASIP Journal on Wireless Communications and Networking, 2013. [22] Investopedia, “(2015),” DEFINITION OF ’PROFIT’. Retrieved October, vol. 15, 2015. [Online]. Available: http://www.investopedia.com/terms/p/profit.asp [23] Marketing Finance, “(2014),” Customers As A Resource. Retrieved October, vol. 15, 2015. [Online]. Available: http://www.type2consulting.com/2014/02/12/customers-as-a-resource/ [24] Bigbelly Solar Inc., “Smart waste & recycling system,” 2015. [Online]. Available: http://bigbelly.com/solutions/ [25] Bloomberg

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Chapter 12

MTC Value Network for Smart City Ecosystems Amirhossein Ghanbari, Óscar Álvarez, Jan Markendahl In IEEE Wireless Communications and Networking Conference (IEEE WCNC) Workshop on “5G Enablers & Applications, pp. 176–181, Doha, Qatar, April 2016.

2016 IEEE Wireless Communications and Networking Conference WS 6 : IEEE WCNC'2016 Workshop on 5G & Vertical Industry - WS 11 : IEEE WCNC'2016 Workshop on The Tactile Internet: Enabling Technologies and Applications

MTC Value Network for Smart City Ecosystems Amirhossein Ghanbari, Oscar Alvarez, Jan Markendahl Department of Communication Systems (CoS) School of Information and Communication Technology (ICT) KTH Royal Institute of Technology, Stockholm, Sweden {amigha, oaa, janmar}@kth.se

Abstract—Looking for new markets and revenue streams, the future Smart Cities comprise a good opportunity for traditional actors of the telecommunication industry. This opportunity requires a new mindset among these actors that corresponds to re-positioning in the Smart City value chain. This means that, in order to play a role that can not be overlooked, Telecom actors should perform rather different blocks of the Smart City value chain compared to their traditional activity blocks in Mobile Telephony value chain. The Fifth Generation of mobile telecommunications technology (5G), by some actors, is then considered as the major ICT enabler for this new paradigm. This paper intends to highlight the role of Machine Type Communications (MTC) for enabling Smart Cities. In order to do so, we introduce the building blocks of Smart City followed by four use cases from Intelligent Transport Systems and Digital Built Environment. We use these cases as the proof of concept for defining the generic MTC activities in the context of Smart City. Eventually the paper introduces the MTC value network in the context of Smart City, based on the resources associated with the activities. Index Terms—5G, Machine Type Communication, MTC, Smart City, Value Chain, Value Network.

I. Introduction A sustainable Smart City is often defined as an innovative city that uses Information and Communication Technology (ICT) and other means to improve quality of life, efficiency of urban operation and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social and environmental aspects [1]. The question then would be what is the role of ICT in this “smartization” process? In this sense, what is commonly required/asked from ICT is typically a “supernatural” platform that does many things, like sensing, connecting machines, collecting data, making smart decisions, and commanding back the machines. But focusing on the communication part, the role of ICT on one hand is to collect information from the machines and send them to the applications; and on the other hand it should transfer the “smartness” from applications to machines. Considering 5G as the paradigm shift in ICT that is supposed to enable Smart Cities, this system should

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include many high technical requirements that are highly integrative with other industries. This integration then happens via Machine to Machine (M2M) communication solutions. The role of M2M solutions is then to sense, analyze and integrate the key information of core systems in running cities. As a result, the relevance of ICT in Smart Cities is twofold: first, how to enable a horizontalization platform for other industry verticals and second, integrating ICT infrastructure in other industries involved. In this article we focus on the latter. Looking into the Smart City ecosystem, the network of suppliers [2] includes ICT providers and subsequently M2M providers. Considering M2M technologies as the enabling ICT tool for cities to become smart, then MTC would be the part where Cellular Telecommunication Networks come into the play (Figure 1). This highlights the role of Telecom actors in Smart Cities. Different actors are trying to position themselves in the M2M market by providing variant sets of solutions, including information management, network deployment, system integration and so on [3]. As a result the M2M ecosystem includes traditional telecom actors and new actors that are also seeking for strong positions, targeting different roles. This creates a complex situation that becomes a challenge for 5G to happen. In this context, this paper aims to provide useful insights on how actors in provisioning MTC are related to each other and ultimately identify Who does what. In order to clarify the topic of the paper, the following research question is introduced: • Where is the place for the Telecom Actors in the Smart City ecosystem? The rest of the article is structured as follows: Section II describes the methodology followed by Section III that introduces the relevance of MTC in Smart City. In this section we present four use cases which belong to two major building blocks of Smart Cities. Section IV then, based on the usecases, describes the MTC activities in this context and identifies their related resources. In section V, we introduce the MTC actors in Smart City and present a generic model for MTC value Network in Smart Cities. Section VI then concludes the article by answering the research question.

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Fig. 2: Sample Smart City value chain

Fig. 1: Sample MTC Architecture based on ETSI M2M II. Methodology The methodology includes a two-stage approach. The first stage provides information on practices of M2M based “smart” solutions for Smart Cities. We use the “ARA model” [4] as a framework to analyze four use cases in the context of Smart City. The ARA model focuses on identifying M2M Activities, Resources associated with them, and Actors who perform activities based on the resources. The second stage provides an analysis with the objective to identify recurring patterns across different cases. The analysis is focused on producing insights into how MTC actors cooperate and distribute their roles, and also to identify and understand drivers and obstacles for introduction of repositioning and cooperation strategies. For analyzing data, Analytic Induction and Grounded Theory methods will be used [5] [4]. These two are iterative methods that alternate between collections and analyses. The iterations continue until no cases dismiss the hypothesis or theory. Analytic induction stops when the hypothesis and grounded theory ends with a validated theory. Value Analysis and Empirical Data Analysis will be performed. The value analysis framework consists of conducting content analysis of collected data and studied literature in order to understand the context of the actors’ decisions, intention and opinion. On the other hand, Empirical Data Analysis framework will be mainly used in order to perceive the current situation in the market and major drawback of implementing a coopetetive system. III. MTC in Smart Cities M2M and MTC are at times considered synonyms. M2M is defined as a set of wireless and wired communication between mechanical or electric devices or the communication between remote machines and central management applications [2]. In a broader scope, M2M includes all the information and communication technologies able to measure, deliver, process and react upon information in an autonomous fashion. Since MTC is the working terminology by 3GPP, it is regarded as the segment of M2M carried over cellular networks [2]. MTC in Smart Cities then refers to the exchange of information over cellular networks

between autonomous devices in control and monitoring applications without human intervention [6]. An oversimplified Smart City value chain is illustrated in Figure 2. This chain mainly corresponds to ICT enabled Smart City solutions where the role of M2M and MTC is quite highlighted. Since it is impossible to map all performed M2M activities in this chain, we rather dig deeper into Smart City based M2M/MTC activities, find out related resources, and eventually identify the value networks for MTC in Smart Cities. Trying to map MTC value network into the Smart City ecosystem, first we define five different building blocks for the Smart City concept [7]: 1) Economic, Social & Privacy Implications 2) Developing E-Government 3) Health, Inclusion and Assisted Living 4) Intelligent Transportation Systems 5) Digital Built Environment This way it is possible to navigate among various MTC enabled use cases in Smart Cities and identify the main activities being performed. In this paper we chose two use cases from Intelligent Transportation Systems, and two from Digital Urban Environment. In this section each use case is described and major MTC activities performed are identified. A. Intelligent Transportation Systems ITS definition: Intelligent Transportation Systems (ITS) can be defined as the application of advanced information and communications technology to surface transportation in order to achieve enhanced safety and mobility while reducing the environmental impact of transportation. • Connected Vehicle Services In this paper we will focus on one specific service within ITS; Connected Vehicle Services. Connected Vehicle Services is commonly defined as the set of services based on ICT and provided during the driving experience. This category includes a number of services including: Remote diagnostics, eCall (Emergency call), MediaroomInfotainment or Insurance billing In the context of Connected Vehicles Services provisioning, a number of activities have been identified. The main activities identified are: Connectivity provision, SIM card provision, Platform management and provision,0 and user management and relationship. Considering these main activities, we can observe different setups regarding collaboration between actors providing these services. In order to illustrate these different setups we will briefly describe two already existing services: Volvo Connected Car, and Tesla Motors.

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recreate on a day to day basis. It provides the setting for human activity, ranging in scale from buildings and parks or green space to neighborhoods and cities that can often include their supporting infrastructure, such as water supply or energy networks. Closely connected with energy efficiency in built environment, this building block also includes Energy Efficiency and Smart Grids. •

Fig. 3: Tesla VS. Volvo

Volvo Connected Car Volvo is currently offering a service named Volvo Sensus connect, which basically is a commercial offering embedded in Volvo vehicles that allows the user to obtain services related to and enabled by ICT. This concrete commercial offering has been commercialized in the US. The setup for the Volvo Sensus connect has been aiming to enhance collaboration between a number of actors, allowing each actor to focus on its field of expertise. The activities are distributed as follows: AT&T is taking care of connectivity and SIM card provisioning, Ericsson is in charge of monitoring, management and automating connected devices deployment, and Volvo is providing end-user management. On top of the Volvo Sensus platform, Over The Top (OTT) providers can offer their own services. An example of these services are media streaming services like Spotify or Netflix. The value network is shown in figure 3 - Right. Tesla Motors Being one of the most innovative car manufacturers in the world and aiming to disrupt how the car industry works, Tesla Motors has a slightly different approach regarding Connected Vehicle services. Tesla Connected services are taking this concept one step further, fostering ideas like software updates enabling autonomous driving in passenger car. The concrete case we are considering is the service offering for the Nordic region. In addition to be a cutting-edge car manufacturer, Tesla has selected a different approach when developing Connected Vehicle services. Tesla’s strategy has been integrating and controlling all possible activities vertically. Therefore Tesla concentrates activities on end-user management and in monitoring, managing and automating connected devices deployment; leaving connectivity provision and SIM card provision in hands of Telia. In a similar way as the previous use case, OTT providers are enabled to provide their services on top of Tesla platform. The setup for the Tesla motors use case is shown in Figure 3 - Left. B. Digital Built Environment Broadly defined, the term Built Environment refers to the human-made space in which people live, work, and

Smart Grids:

Smart Energy or Smart Grid is one the most important aspects of the Smart City concept, enabling responsible management and operation of energy networks in cities. The integration of communication infrastructure, mathematical modeling techniques and simulation techniques is a powerful tool in this context. The concept of Smart Grid also includes the idea of “prosumers” that is the idea of integrating decentralized energy generation in nowadays’ centralized energy grids, enabling households to produce their own energy and sell/buy from the energy grid depending on their consumption. This also holds for the potential storage capacity for both electrical and thermal energy within energy networks, which can be achieved by intelligent demand side management [8]. A major requirement in Smart Cities in this regard is to leverage energy consumption between different producers and consumers that directly translates into reducing the pollution generated by today’s cities and the emerging mega cities [9]. Consorcio Energ´ etico Punta Cana Macao (CEPM) The Dominican Republic has been facing a number of energy challenges in recent years, related to substandard service, inadequate capacity and frequent black outs. These challenges are also connected to its increasing importance as a tourism destination. In order to tackle these challenges the sector has gone through a process of liberalization, where companies like CEPM have provided innovative energy solutions. One of the services provided by CEPM is: reliable Advanced Metering Infrastructure (AMI) solution which would withstand rigorous power fluctuations and provide remote monitoring and management of its electrical grid. Together with General Electrics Digital Energy and Ingenu, CEPM has enabled over 24,000 smart meters to speed power restoration and increase reliability of services to CEPM’s customers. The solution offered robust, twoway communication between CEPM and its end users, providing accurate reporting and monitoring of energy operation and consumption. Due to its limited infrastructure investment, CEPM was able to deliver energy services cost-effectively, resulting in significant savings to its customers. In this setup Ingenu plays the role of connectivity provider and GE Digital Energy provides different devices needed i.e. smart meters. The underlying communication technology used to enable these services is Random Phase Multiple Access

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(RPMA), a low-power wide-area channel access method used exclusively for M2M communications. •

Waste Management:

Smart Waste is part of the smart city concept, focusing on municipal solid waste. Navigant Research defines Smart Waste as the integration of advanced technologies into a strategic solution that enhances sustainability, resource efficiency, and economic benefits. The use of these technologies result in more integrated waste management offerings that go beyond the traditional use of labor, diesel trucks, and open pits to discard waste. Waste management is getting smarter as new technologies are implemented in different areas. Here we focus on applications of Smart Waste making use of M2M technologies. Early experiments with M2M type solutions in waste management industry involve a scale for measuring the mass of waste in the garbage truck - or similar before emptying the load at the waste station. The waste management system is seeing rapid changes. The change from landfills to incineration is shaping the structure of the system from municipal into larger areal networks. This will have an effect on how waste management is organized, what technology is used and how business is done. Today there is, however, limited evidence of new M2M based solutions being developed/implemented [10]. Bigbelly Solar Inc. BigBelly Solar Inc. provides solutions for the management of waste and recycling. It offers solar intelligent waste collection systems to manage the process of collecting solid waste, as well as solar compactors, and companion recycling bins and kiosks. CLEAN™ by BigBelly is a wireless network for monitoring and management software that provides real-time and historical data to managers/workers to plan waste collection routes and pickups; Connect™ is a turnkey smart waste and recycling system that ensures customer engagement and satisfaction. It serves municipalities, cities and towns, college and university campuses, parklands and beaches, government and military installations, and institutional customers [11]. An elaboration on how Bigbelly works as a system in the US is as follows: • •

• •

Compactors are upgraded with wireless hardware. CLEAN sends data through standard SMS format to its online server (requires adequate cellular phone signal, currently provided by AT&T). Operational data becomes real-time. Collecting is monitored to eliminate unnecessary pickups and free up workers from on-street status checks.

In order to provide these services the activities are distributed as follows: AT&T providing connectivity and SIM card provisioning, Ericsson in charge of monitoring, management and automation of connected devices deployed and Bigbelly handling device provision and software ser-

Fig. 4: Bigbelly vs. CEPM vice provision (visualization and management tools for cities). This setup is shown in Figure 4 - Left. IV. MTC Activities & Resources In this section we introduce a set of generic activities associated with M2M solutions offered in the Smart City context. Afterwards, we discuss the “M2M resources” associated with these activities. These activities are based on studied usecases. The main idea is that these activities cover all major MTC activities performed in such setups. The constructed model for these roles has then the ability to map all different possible M2M solutions into it. This way we create a framework (Figure 5) for analyzing the activities and identify which activity is being performed by its corresponding actor, based on the possessed resources. The generic activities related to M2M and subsequently MTC are as follow: 1) Provision MTC network 2) Provision M2M device 3) Provide Connected Device Platform (CDP) 4) Provide Application Enablement Platform (AEP) 5) Provision M2M service 6) Manage Customer relation This framework first categorizes the activities into three domains; a) Service, b) Connectivity, and c) Device. Each domain here directly translates to aforementioned Figure 1. Since two major activities correspond to “M2M Platforms” first we discuss what is meant by M2M Platform. A. M2M Platforms An important part of the M2M ecosystem comprises the platforms, which includes CDP and AEP [12]. Correspondingly, provisioning these two platforms is considered as major roles in the value chain. 1) CDP: Connected Device Platform: CDPs are software elements that facilitate deployment and management of connected devices for M2M applications over cellular networks. CDP allows devices to connect to Cloud and should be compatible with different software platforms (e.g. Java, Android, etc.) in order to include as many devices as possible. CDP is usually a service portal that covers billing and policy control, bearer service, service ordering and subscription, and SIM-card management.

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Fig. 5: Relation among MTC activities in Smart City 2) AEP: Application Enablement Platform: AEPs are designed to provide the core features for multiple M2M applications. They ease the data extraction and normalization activities, so M2M applications and enterprise systems can easily consume machine data. AEP also includes developing tools, enabling developers to create new M2M applications and services. B. MTC Resources When it comes to the role of ICT in Smart City, a set of resources enable the MTC actors to participate and perform different sets of activities. The importance of these resources lies in the fact that missing these resources disables an actor to perform a specific activity. By a resource it is meant anything which could be thought of as a strength or weakness of a given firm. More formally, a firm’s resources at a given time could be defined as those (tangible and intangible) assets which are tied semi permanently to the firm [13]. Examples of resources are: brand names, in-house knowledge of technology, employment of skilled personnel, trade contacts, machinery, efficient procedures, capital, etc. [14]. Defined pedagogically, resources can be categorized into six major categories [15]; financial, physical, human, technological, organizational, and reputation. 1) MTC Infrastructure: When providing communication services, the need of communication networks appear naturally. Within communication networks two different types can be identified: Core Network and Cellular Access Network. The core network is the central part of the communications network, facilitating the connection between different sub-networks. The cellular access network (also known as radio access network) is the interface between the end-user and the core network, basically using wireless technology. The MTC Infrastructure is traditionally owned by a MNO, since it is the same as the mobile telephony cellular infrastructure. In the introduced cases, we also have seen emerging actors

who are specialized MTC Network Operators who own their own infrastructure. 2) Application Enablement Platform: A software platform that acts as a common ground for development of services and applications on top of the physical infrastructure. AEP can also provide an open environment for collaboration between industries and support innovation in the context of smart sustainable cities. 3) M2M Data: One very important resource when introducing Smart City and M2M services is the data originated for the End Users in the city. Data can be defined as all the information obtained from the usage of a number of services in the city environment; communication, Internet services, transportation services, energy consumption, car-sharing, parking, logistics, etc. The added value in Smart City comes from obtaining a big amount of data, processing it and extract useful information for decision making. 4) End-user: The final goal of these services is to provide useful information and services to the End User, whom will be able to make better decisions on how to interact with the city. In the provisioning of services, a number of actors are involved and it is not feasible that the End User has relation with all of them. The usual relations with the user are with either the service provider or the M2M device provider (in some cases). In this sense, different stakeholders are sharing this resource event though not all of them have direct relation with it. It could be concluded that customers are the economic resource which are subject to be cultivated by the producer [10] [16]. V. MTC Actors in Smart City Since MTC corresponds to utilizing cellular technologies as the access network for M2M services, traditional actors in the mobile telephony value network are viably active here as well. Mobile Network Operators (MNO) as the typical carriers that control and operate cellular networks are capable of operating the MTC network. Telecom Equipment Vendors (TEV) as the traditional manufacturers of the telecommunication equipment, typically provision the technical procurement for the MNOs. But, according to the shift in the value chain, the TEVs have recently participated in different roles that historically have been assigned or taken care of by others; such as MNOs. Even roles like provisioning new demands such as Connectivity Platforms are now being provisioned by some TEVs. Figure 6 illustrates the major business relations for MNOs and TEVs in the Mobile Telephony case. A Managed Service Provider (MSP) is typically an entity that offers end-to-end solutions; such as network operation management in this case. Based on proposed MTC Activities, Resources, Actors, and most importantly the framework introduced in figure 5, five major groups of actors can be identified in the MTC value network. Besides the End

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Fig. 6: Traditional Value Networks of Mobile Telephony Users (EU), these actors are the most likely entities who can own either of the resources mentioned earlier in order to perform MTC activities. These actors are: a) End User, b) Service Provider, c) MTC network operator, d) Device Provider, and e) MSP. According to the cases studied earlier, we showed that rather than traditional Telecom actors (i.e. MNOs and TEVs), there are other actors who might be even more competent in provisioning any of the activity blocks of MTC. For instance, a specialized M2M cellular network operator (MTC network operator) can be considered a better option to provision MTC network. Service Providers of M2M solutions also in some cases take control of the entire value chain by handling the EU; a previously dominant position for MNOs in Mobile Telephony (Figure 7 - Right). On the other hand, TEVs and MNOs have shown interest in different activity blocks. Another major actor in this setup is then an entity which performs the role of provisioning CDP. It can be seen that this activity is mainly performed by the firms who have a history in provisioning connectivity in the sense of automating connected devices. Some examples can be either outsourcees of network operations for MNOs (MSPs) or the ones which have been active in automation of industry verticals (e.g. General Electrics, Siemens, etc.). VI. Conclusion Figure 7 illustrates two major setups of the MTC value network in Smart Cities. According to our description of the MTC activities, telecom actors are capable of performing multitude of activities in MTC value network in Smart Cities, but based on their resources. This directly concerns the competences they can acquire and/or have. Considering “connectivity domain” as their main playground, provisioning AEP is also an activity being performed by some TEVs in recent years. This way, telecom actors mainly correspond to either MTC network operators and/or MSPs (supporting role for provisioning AEP, CDP). An interesting observation here is the absence of MNOs on “owning” the End User. In terms of resources, it is important to consider that the actor who owns the end user -as a resource- is the most likely to have control over the value network. This value network should be considered when developing/deploying 5G systems, as it should allow collaborative setups to happen. Finally, it could be concluded that 5G and ICT will play the enabler-support role for making Smart Cities happen and not much more; so would the telecom actors.

Fig. 7: Two major setups of MTC Value Network Acknowledgment Part of this work has been performed in the framework of the H2020 project METIS-II co-funded by the EU. The views expressed are those of the authors and do not necessarily represent the project. The consortium is not liable for any use that may be made of any of the information contained therein. References [1] ITU-T Focus Group on Smart Sustainable Cities, “Smart sustainable cities: An analysis of definitions,” 2015.11.01 2014. [2] A. Laya, A. Ghanbari, and J. Markendahl, “Tele-economics in mtc: what numbers would not show,” EAI Endorsed Transactions on Internet of Things, vol. 1, no. 1, 10 2015. [3] A. Laya, V.-l. Bratu, and J. Markendahl, “Who is investing in machine-to-machine communications?” in 24th European Regional Conference of the International Telecommunication Society. Econstor, Conference Proceedings. [4] A. H˚ akansson, “Portal of research methods and methodologies for research projects and degree projects,” in The 2013 World Congress in Computer Science, Computer Engineering, and Applied Computing WORLDCOMP 2013; Las Vegas, Conference Proceedings, pp. 67–73. [5] I. Snehota and H. Hakansson, Developing relationships in business networks. Routledge Londres, 1995. [6] G. Wu, S. Talwar, K. Johnsson, N. Himayat, and K. D. Johnson, “M2m: From mobile to embedded internet,” Communications Magazine, IEEE, vol. 49, no. 4, pp. 36–43, 2011. [7] L. M. Correia and K. W¨ unstel, “Smart cities applications and requirements,” White Paper. Net, 2011. [8] U.S. National Energy Technology Laboratory, “A vision for the smart grid,” 2015.11.01 2009. [9] O. Alvarez, “Business transformation based on ict: Smart grid,” M.Sc. Thesis, 2014. [10] A. Ghanbari, O. Alvarez, T. Casey, and J. Markendahl, “Repositioning in value chain for smart city ecosystems, a viable strategy for historical telecom actors,” 2015. [11] Bigbelly Solar Inc., “Smart waste & recycling system. retrieved from the bigbelly solution,” 2015. [Online]. Available: http://bigbelly.com/solutions/ [12] S.-S. Manfred and N. Dmitry, “On m2m software platforms,” International Journal of Open Information Technologies, vol. 2, no. 8, 2014. [13] R. E. Caves, Industrial organization, corporate strategy and structure. Springer, 1992. [14] B. Wernerfelt, “A resource-based view of the firm,” Strategic management journal, vol. 5, no. 2, pp. 171–180, 1984. [15] R. M. Grant, “The resource-based theory of competitive advantage: implications for strategy formulation,” Knowledge and strategy, vol. 33, no. 3, pp. 3–23, 1991. [16] Marketing Finance, “Customers as a resource,” 2015.11.01 2014. [Online]. Available: http://www.type2consulting.com/2014/02/12/customersas-a-resource/

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Chapter 13

Value Creation and Coopetition in M2M Ecosystem - The Case of Smart City Amirhossein Ghanbari, Andrés Laya, Jan Markendahl In 27th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (IEEE PIMRC) - Workshop on “From M2M Communications to Internet of Things”, Valencia, Spain, September 20161 .

1 Accepted

paper.

Value Creation and Coopetition in M2M Ecosystem - The Case of Smart City Amirhossein Ghanbari, Andres Laya, Jan Markendahl Department of Communication Systems (CoS) School of Information and Communication Technology (ICT) KTH Royal Institute of Technology, Stockholm, Sweden {amigha, laya, janmar}@kth.se

Abstract—Wireless ICT as a subcategory of the ICT industry has long been serving end users as its direct customers. The value for end users, i.e. connectivity as the end product of this industry, has been created in a linear chain where two major group of actors have been cooperating with each other: Telecom Equipment Vendors (TEV) and Mobile Network Operators (MNO). By the demand of other industries for connecting devices/machines in order to enable various services, Machine to Machine (M2M) communications and Internet of Things have emerged as new concepts where Wireless ICT could serve other industries. As a result “connectivity” became an enabler (service) and not the final product. In this paper we argue that linear telecom value chains are incapable of serving this new demand, since wireless ICT requires to co-create value with other industries. This causes the formation of telecom value networks in which traditional telecom actors have to form new (different) business relationships with each other; Cooperation with competitors and Competition with cooperators. Index Terms—Coopetition, Co-creation, M2M, MTC, Smart City, Value Chain, Value Network.

I. Introduction As a means of enhancing our everyday lives, as well as a transformation tool for other industries, the Information and Communication Technology (ICT) industry has experienced a significant transformation during the past two decades [1] [2]. On one hand, this transformation relates to technological advances. On the other hand it goes beyond the ICT ecosystem, where the role of the actors and the relationships among them has been changing. Telecommunication industry–Wireless ICT–, as a subcategory of ICT industry, is no exception in this regard. If we consider Mobile Network Operators (MNO)1 and Telecom Equipment Vendors (TEV)2 as the major telecom actors in the past; these firms have experienced, and created, many changes in their business in order to adopt/cause 1 Examples of MNOs are Vodafone Group, AT&T Mobility LLC, and Telef´ onica S.A. 2 Examples of TEVs are Ericsson and Alcatel-Lucent S.A.

this transformation; not to mention that new actors who entered this ecosystem have also forced some changes to the ecosystem. With regards to the presence of ICT in other industries, these new actors are mainly the industry vertical Service Providers (SP) offering telecom-enabled services3 and Over the Top (OTT) service providers4 . When it comes to the formation of the “future telecom” ecosystem, in the presence of other industries, we introduce an uncertainty that is the changes in relationships among different actors. If we consider MNOs, TEVs, and SPs as the major actors of the present telecom service provisioning ecosystem, this uncertainty boils down to the relationships among them. Different patterns of interaction among such actors have been observed. Cooperation among competing MNOs due to lack of resources, or competition over providing services among cooperating MNOs and TEVs are instances of these relationships. This paper is build on top of our recent work, “MTC Value Network for Smart City Ecosystems” [3], where we introduced a framework in order to study the Machine Type Communication (MTC) and M2M activities in different setups. Based on this framework and case studies presented, we were able to introduce an abstract value network for M2M activities in the context of Smart City. As a continuation, in this paper, we discuss the business relationships among different actors of the introduced value network. We use the value network framework together with data from case studies and question what would happen if any of the three groups of actors under study– MNOs, TEVs, and SPs–perform either of the abstract activities introduced in the framework. We use Porter’s five forces model (P5F) as a checklist for identifying important business relationships for the focal firm and try to determine the positions in which MNOs, TEVs, and SPs 3 An example of a SP is an Automotive company that, together with the aid of a MNO and a TEV, offers Connected Cars to its customers. 4 OTT SPs, typically, offer services on top of an existing system/infrastructure. An example of an OTT SP is a “commercial music streaming company” that offers its services to the passengers of the Connected Car, over the top of the car’s Infotainment Center.

would possibly compete with each other and/or cooperate [4] [5]. In this context, this paper aims to provide useful insights on how M2M/MTC actors create value while they enter other industries as enabler/providers. In order to clarify the topic of the paper, the following research question is introduced: • Where is the coopetition for the Telecom Actors in the Smart City ecosystem? II. Methodology The methodology includes a two-stage approach. The first stage provides information on practices of M2M based “smart” solutions for Smart Cities [6]. In [3] we introduced four case studies of Smart City solutions enabled by M2M/MTC, where they work as a basis for analysis in this work as well. We use the “ARA model” [7] as a framework to analyze the four use cases in the context of Smart City. The ARA model focuses on identifying M2M Activities, Resources associated with them, and Actors who perform activities based on the resources. The second stage provides an analysis with the objective to identify recurring patterns across different cases. The analysis is focused on producing insights on how actors cooperate and distribute their roles, and also to understand drivers and obstacles for their cooperation strategies. We also use Porter’s Five Forces (P5F) framework for analyzing the market and identified business relationships. The framework looks at five specific factors that make a qualitative evaluation of a firm’s strategic position, based on other firms in the industry [8]. Hence, we use this framework as a checklist to identify important business relationships that the focal firm has while considering competition and cooperation with other firms in the industry/market. For analyzing data, Analytic Induction and Grounded Theory methods will be used [9] [7]. These two are iterative methods that alternate between collections and analyses. The iterations continue until no cases dismiss the hypothesis or theory. Analytic induction stops when the hypothesis and grounded theory ends with a validated theory. Value Analysis and Empirical Data Analysis will be performed. The value analysis framework consists of conducting content analysis of collected data and studied literature in order to understand the context of the actors’ decisions, intention and opinion. On the other hand, Empirical Data Analysis framework will be mainly used in order to perceive the current situation in the market and major drawback of implementing a coopetetive system. III. M2M activities in Smart Cities M2M and MTC are at times considered synonyms. M2M is defined as a set of wireless and wired communication between mechanical or electric devices or the communication between remote machines and central management applications [4]. In a broader scope, M2M includes

Fig. 1: Framework to study activities in M2M ecosystem [3] all the information and communication technologies able to measure, deliver, process and react upon information in an autonomous fashion. Since MTC is the working terminology by 3GPP, it is regarded as the segment of M2M carried over cellular networks [4]. MTC in Smart Cities then refers to the exchange of information over cellular networks between autonomous devices in control and monitoring applications without human intervention [10] in order to make “smartization” possible by the aid of M2M and MTC. The so-called M2M/MTC-enabled services then are the main tools that make the cities smart. The connectivity side of this enablement then sounds like the promise of Fifth Generation of mobile networks (5G). When it comes to the demands from Wireless ICT as a provider of M2M/MTC, it is important to discuss what does the new generation of mobile networks (i.e. 5G) is promising that previous generations (e.g. 4G) did not enable? The answer is to think of 5G as of an improved generation, not only technically but mainly in Business domain; a sliced network that accommodates industry verticals and helps them horizontalize. This means that 5G is more about the demand and less about a push from technology and not only about telecommunication technology any more. Focusing more on service provisioning, and XaaS (Everything as a Service), connectivity then becomes a service enabler, while not long ago connectivity was the only service. This means that the “future telecom” is about to expand its market, more, to other industries as well as creating new market/s. Therefore, if this new market wants to happen, value needs to be created together (cocreation) with others: (a) Internally, which is among telecom actors, and (b) Externally, which is among telecom actors and actors of the other industries. The question is then how would be the relationships among firms in this new setup? Looking into provisioning M2M-enabled services we di-

vide M2M activities into three main domains, based on “ETSI M2M simplified architecture”. These domains are Service , Connectivity, and Device (Figure 1). In each domain there are some activities that are performed by providers and one activity that is performed by the end user. All the end user activities then comprise one horizontal layer that corresponds to the Customer Relation Management (CRM) activity. The CRM activity is typically performed by the actor who is in direct connection to the end user. Therefore, figure 1 presents a framework to study M2M activities. The framework illustrates the relations among activities in terms of inter-dependencies, as well as the sequence of activities to be performed. The main idea behind implementing this formation is to present the value flow [11]. This framework will eventually facilitate the process of distributing responsibilities among actors and also helps identifying the actors and possible grouping of activities to be performed by any actor. According to the framework (figure 1) each activity can be performed by one actor in the value network, while the end value is being co-created by the entire network. This idea is also approved by the case studies presented in [3]. The only concern is then provisioning the Application Enablement Platform (AEP) [12], where the case studies show that AEP is typically provisioned together with the service and in some few instances as a complement to the Connected Device Platform (CDP) [12]. Therefore the role of AEP provisioning is not a stand-alone role in the value network. As a result we introduce the following abstract actors: • • • •

MTC network operator M2M/MTC device provider MSP OTT service provider

A major actor in this setup is then an entity which performs the role of provisioning CDP. It can be seen that this activity is mainly performed by the firms who have a background in provisioning connectivity in the sense of automating connected devices. Some examples can be either outsourcees of network operations for MNOs or the ones which have been active in automation of industry verticals (e.g. General Electric, Siemens, etc.). The socalled Managed Service Partner (MSP) actor is the firm that takes this role. It should be mentioned that AEP provisioning, in case of bundling as a complement to CDP, is also performed by this actor. Eventually, we introduce two abstract M2M value network instances (Figure 2 that illustrate MTC-based mobile service provisioning. In these networks the abstraction is on the firm level that means any actor who owns the resources-competences associated to each activity can perform the activity. The major difference between these two instances is the interaction with end user. In the model on the right, the SP is the firm that interacts with the end user. This happens when the device is part of the service

Fig. 2: Two M2M Value Network instances in Smart Cities [3] TABLE I: Who is capable of what? MNO MTC network Provisioning

Actors TEV

MTC device offering CDP provision AEP provision

SP

X X* X

X X

X

Offer M2M-enabled service

X

End User relation management

X

*This situation happens in case SP is the industry vertical service provider.

and the main value is delivered by the service and not the device. An example is the case of smart meters. The electricity meter is typically offered to the end user by the energy company, although the energy company is offering the device as part of the service (that is metering energy consumption). The model on the left then presents a case where the device provider initiates the relationship with the end user by offering the device, since the device itself bears a value of its own. The device provider then maintains this relationship via offering M2M-enabled service as an add-on (e.g. M2M services offered on personal vehicles). In this case, the services over the top of this device are also being offered through the device provider to the enduser, which means without this channel there is not a possible way to offer the OTT services to the end user. The device provider holds the role of interacting with the end user, mainly because of the notion of the device (as a platform for services). This case can mainly happen when the device provider is the industry vertical solution provider itself, and is offering services of its own (the case that we formerly called it SP). For instance when an automotive company is offering a “connected car”, the car as a the M2M device is holding a high value in the service provisioning and also serves as a platform for other services to be offered on top of it. This situation is typically profitable for the device provider in case they have an ongoing relationship with the end user, which is gained via a M2M-enabled service by the device provider/SP itself. The three actors under study –MNO, TEV, and SP–

typically take different roles from the aforementioned value network based on their business models. On one hand the resources these actors possess, as well as the competence to perform the activity is a major reason that they play any specific role. On the other hand, other reasons such as where to position the firm in the value network, who to compete with, who to collaborate with, and external forces also affect the strategic decision of which role/s to take. Therefore, here we present a table illustrating what are these actors capable of, according to their traditional business and resources/competences (Table I). IV. Business Relationships within a value network context In this section we discuss the business relationships among different actors of the value network introduced earlier. We use Porter’s five forces model as a checklist for identifying important business relationships for each group of actors under study (focal firm). As a result of this analysis we determine the positions in which MNOs, TEVs, and SPs would possibly compete with each other and/or cooperate. In order to use the P5F model, first we put the forces into the telecom industry context and discuss them in general in the context of our study. 1) Threat of New Entrants In the old telecom value chain, as a capital-intensive industry, the biggest barrier to entry was access to finance. In the future telecom industry, where telecommunication plays the role of enabler for services, the situation is different. When services co-created by multiple actors, or services created over the top of other products bear the value, the threat of competitive entrants escalates. Not like before, ownership of a telecom license does not necessarily represent a huge barrier to entry. This is because there is probably a license holder who is willing to cooperate with the SP in order to create the value. 2) Power of Suppliers In the context of value networks, unlike value chains, suppliers have a less critical position. At the same time there are actually large number suppliers around willing to become part of the telecom-enabled service. Vendors, arguably, are not the sole supplier of the value chain any more. MNOs, Vendors, IT companies and even Service Providers in different settings become suppliers to each other since the creation of value does not follow the same linear chain any more. As a result, the bargaining power of suppliers is diluted. 3) Power of Buyers With introduction of variety of telecom-enabled services and demand oriented service provisioning, the bargaining power of buyers rises. Traditional telecommunication services such as connectivity have become a commodity and their availability can be taken for granted. This translates into customers seeking low prices from companies that offer reliable service. Switching costs are relatively lower

for end user but higher for those in need of customized solutions, but still buyers intend to avoid lock-in and vendor lock-in effects. At the same time, due to the power of business customers who own a considerable share of end users, suppliers tend to offer tailored solutions for their customers, just not to lose the revenue. 4) Availability of Substitutes Services from non-traditional telecom actors pose serious substitution threats over traditional products/services. Specialized actors who focus on a specific activity and target niche markets also have emerged that their services are comparatively well designed. At the same time, some traditional actors step in and perform same activities as their suppliers/buyers in another setting would offer and they can offer the same service to the end user. 5) Competitive Rivalry Competition is fierce. New entrants, previous suppliers overtaking buyers position, previous customers overtaking suppliers position, substitute services made by similar firms, different constellations working together to create value, and more global offerings are enough reasons to worry about competition. Limiting competition to the existing rivals, similar firms and replacement by previous customers/suppliers seem to be the highest threat in terms of competition. Now that we have a better understanding of the five forces, we introduce other possible exiting (traditional) actors that perform the presented activity list mentioned in figure 1 in order to have a complete picture of Suppliers, Customers, and Existing rivals according to P5F. We remind that, as stated before, the industry vertical solution providers are the same entities as SPs. OTT service providers are then the, typically, small businesses that just offer services over the top of the existing infrastructure/services. Besides the discussed actors –MNOs, TEVs, and SPs– the other important actors are: 1) OTT Service Providers (e.g. Spotify, Facebook, etc.) 2) CRM & billing solution providers 3) Software based systems & solutions firms (SBSS). These are typically non-wireless ICT firms (sometimes referred to as IT companies). Such firms in the context of telecom industry mainly offer measurable performance improvements in an operator’s business processes, with software that is scalable, configurable and that provides end-to-end capabilities. The business segment develops and delivers software-based solutions for OSS and BSS, TV and media solutions, as well as solutions and services for the emerging m-commerce ecosystem. We consider that Business Customer Support companies and Consulting and Systems Integration (CSI) companies also belong to this group. 4) Device provider, which refers to companies that manufacture the devices which will be offered to end user

TABLE II: Five forces analysis on MNOs Existing rivals

Suppliers

Customers

New entrants

Subs products

1. MNO

1. TEV

1. Device provider

Specific MTC

Capillary network

2. Capillary network operator

2. SBSS

2. SP

network provider

-

-

-

-

-

1. MNO 2. TEV

1. TEV 2. SBSS




AEP provision

-

-

-

-

-

Offer M2M -enabled service

-

-

-

-

-

CRM

-

-

-

-

-

MTC network provision

MTC device offering CDP provision

TABLE III: Five forces analysis on TEVs Existing rivals

Suppliers

Customers

New entrants

Subs products

MTC network

-

-

-

-

-

MTC device offering

-

-

-

-

-

CDP provision

1. TEV 2. MNO

SBSS




AEP provision

1. SBSS 2. SP

SBSS -

1. SP 2. OTT SP

Specific AEP provider

n/a


-

-

-

-

-

CRM

-

-

-

-

-

TABLE IV: Five forces analysis on SPs Existing rivals

Suppliers

Customers

New entrants

Subs products

-

-

-

-

-

SP

Device provider


n/a

n/a

CDP provision

-

-

-

-

-

AEP provision

1. SBSS 2. SP

n/a

1. Device provider 2. OTT SP

Specific AEP provider

n/a

1. End User 2. Device provider 3. OTT SP

n/a

Other services

n/a

n/a

MTC network provision MTC device offering


CRM

SP

Device provider

1. 2. 3. 4. 5. 6.

MNO TEV Device provider SBSS Specific AEP Specific CDP

n/a

in this value network. This is the same device that is enabled by MTC capabilities. 5) Specific MTC network provider: • Wide area wireless telecom providers: e.g. Sigfox. • Indoor communication providers: e.g. Wi-Fi companies such as Aptilo.


6) Special CDP providers (e.g. Jasper, Sierra wireless, Wyless, etc.). 7) Special AEP provider (e.g. ThingWorx). Now we take the three actor groups –MNOs, TEVs, and SPs– separately and put them in the P5F model. We will do this based on the case studies presented in [3], tableI, and the discussion in the beginning of section IV

(on putting PF5 in the telecom context). We use the list of important actors in order to find possible existing rivals, suppliers, and customers. The results are then presented in tables II, III, and IV, which show the five competitive forces of the market for each group of focal actors. Based on the tables, we can identify the coopetition areas among the three actor groups. As it is illustrated in the tables, on one hand in the “existing rivals” column if any of the three actors (beside the focal actor) exists that means competition. On the other hand, if any actor (besides the focal actor) exists in the Suppliers-Customers columns, that means cooperation among them. We will translate these two instances into Coopetition while both of them happen at the same time. Why are customers important? With regards to the “customers” and “suppliers” columns, we argue that the relationship among any supplier and its customer is quite important for the survival of the supplier’s business. This highlights the risks associated with competing with customers. On economic terms, what is important for a firm is higher profit. Profit is a financial benefit that is realized when, in a business activity, gainedrevenue is more than all expenses (including taxes). The source of the revenue gained by the firm is then the price the customer pays. For a customer, value is defined as the ratio between the benefits they receive and the price they pay. Considering that the Value for a firm (producer) is reflected as financial profit; value is the difference between the revenues they receive and the costs they incur. So more profit for the producer can be gained by: 1) Creating more benefit for customers 2) Increasing the number of customers 3) Lowering expenses Or in other words, “Customers are the economic resource to be cultivated by the supplier”. As a result it is a major concern when a supplier would like to jeopardize profit by causing discomfort in its relationship with customers by competing with them. This is important when competition comes after cooperation; when an existing cooperative business relationship (e.g. supplier-customer) is ongoing and then competition occurs. V. Conclusion While searching for instances of coopetition among telecom actors, an interesting finding is that convergence of wireless ICT actors and other industries for co-creating value in various industries has changed telecom value chains and caused formation of value networks. This change is mainly due to the need to co-create value together with customers, i.e., non-ICT industry service providers (in this case). The need for such cooperation is mainly because of “resource dependency”. Since telecom actors do not possess resources to offer non-ICT services (e.g. Automobiles, Health care, Waste Management, etc.)

to end users, they rather depend on their customers in order to reach end users. As a consequence, vertical cooperation is the key business relationship between telecom actors and non-ICT actors. At the same time, due to presence of telecom industry in a diverse set of industries, these actors do not necessarily follow any “telecom-specific” pattern any more. This is because telecom actors try to adapt to their business customer’s preference in their Business to Business (B2B) transactions, and customers’ respective market structure. In this process the requirements from telecom actors are relatively high, necessitating vertical cooperation among them (e.g.TEVs and MNOs) in order to cooperate on enabling services like IoT for customers in other industries. Eventually, in case these vertical telecom cooperators decide to offer similar services to non-ICT customers, in case they posses or endeavor to posses their cooperators’ resources, there is a risk of competition. We refer to this competition as vertical coopetition in case they cooperate on one service while competing over another service. Acknowledgment Part of this work has been performed in the framework of the H2020 project METIS-II co-funded by the EU. The views expressed are those of the authors and do not necessarily represent the project. The consortium is not liable for any use that may be made of any of the information contained therein. References [1] C. Christensen, S. Anthony, and E. A. Roth, Seeing what’s next: Using the theories of innovation to predict industry change. Harvard Business Press, 2013. [2] M. Fransman, The new ICT ecosystem: Implications for policy and regulation. Cambridge University Press, 2010. [3] A. Ghanbari, O. Alvarez, and J. Markendahl, “Mtc value network for smart city ecosystems,” in 2016 IEEE Wireless Communications and Networking Conference (WCNC), Workshops, Conference Proceedings. [4] A. Laya, A. Ghanbari, and J. Markendahl, “Tele-economics in mtc: what numbers would not show,” EAI Endorsed Transactions on Internet of Things, vol. 1, no. 1, 10 2015. [5] A. Ghanbari, O. Alvarez, T. Casey, and J. Markendahl, “Repositioning in value chain for smart city ecosystems, a viable strategy for historical telecom actors,” 2015. [6] ITU-T Focus Group on Smart Sustainable Cities, “Smart sustainable cities: An analysis of definitions,” 2015.11.01 2014. [7] A. H˚ akansson, “Portal of research methods and methodologies for research projects and degree projects,” in The 2013 World Congress in Computer Science, Computer Engineering, and Applied Computing WORLDCOMP 2013; Las Vegas, Conference Proceedings, pp. 67–73. [8] M. E. Porter, “The five competitive forces that shape strategy.” 2008. [9] I. Snehota and H. Hakansson, Developing relationships in business networks. Routledge Londres, 1995. [10] G. Wu, S. Talwar, K. Johnsson, N. Himayat, and K. D. Johnson, “M2m: From mobile to embedded internet,” Communications Magazine, IEEE, vol. 49, no. 4, pp. 36–43, 2011. [11] O. A. El Sawy and F. Pereira, Business modelling in the dynamic digital space: An ecosystem approach. Springer, 2013. [12] D. Namiot and M. Sneps-Sneppe, “On m2m software,” International Journal of Open Information Technologies, vol. 2, no. 6, 2014.

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